├── .github
└── ISSUE_TEMPLATE.md
├── DESCRIPTION
├── LICENSE
├── NAMESPACE
├── R
├── internal.R
├── metadata.r
├── omicplotr.R
├── omicplotr.run.r
└── otu_table.r
├── README.md
├── data
├── metadata.rda
└── otu_table.rda
├── inst
├── .DS_Store
├── NEWS
└── shiny-app
│ ├── PCA_script.R
│ ├── effect_script.R
│ ├── example_data.txt
│ ├── example_metadata.txt
│ ├── extrainformation.Rmd
│ ├── help.Rmd
│ ├── rab_script.R
│ ├── selex.txt
│ ├── server.r
│ ├── ui.r
│ └── www
│ ├── bootstrap.css
│ ├── colored_biplot.png
│ ├── example_data.png
│ ├── example_metadata.png
│ ├── histogram_colored.png
│ └── metadata_filter.png
├── man
├── internal.Rd
├── metadata.Rd
├── omicplotR-package.Rd
├── omicplotr.run.Rd
└── otu_table.Rd
└── vignettes
├── col_PCA.png
├── effect.png
├── example_data.png
├── example_metadata.png
├── inputdata.png
├── metafilter.png
└── omicplotR.Rmd
/.github/ISSUE_TEMPLATE.md:
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1 | # Please make sure to fill in this template when submitting an issue. Thank you for taking the time to submit an issue!
2 |
3 | - [ ] Check that you are using the newest release of R.
4 | - [ ] Check that you are using the newest release of omicplotR.
5 |
6 | # What OS are you on?
7 |
8 | - [ ] Windows
9 | - [ ] macOS
10 | - [ ] Linux
11 |
12 | ### What version of your OS are you on?
13 |
14 | # Expected Behaviour
15 |
16 | What is the expected behaviour?
17 | What is the actual behaviour?
18 |
19 | # Steps to reproduce the behaviour:
20 |
21 |
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/DESCRIPTION:
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1 | Package: omicplotR
2 | Title: Visual Exploration of Omic Datasets Using a Shiny App
3 | Version: 1.7.1
4 | Date: 2019-11-12
5 | Authors@R: c(person("Daniel", "Giguere", email = "dgiguer@uwo.ca", role = c("aut", "cre")), person("Jean", "Macklaim", role = "aut"), person("Greg", "Gloor", role = "aut"))
6 | biocViews: Software, DifferentialExpression, GeneExpression, GUI, RNASeq, DNASeq, Metagenomics, Transcriptomics, Bayesian, Microbiome, Visualization, Sequencing, ImmunoOncology
7 | Description: A Shiny app for visual exploration of omic datasets as
8 | compositions, and differential abundance analysis using ALDEx2. Useful for
9 | exploring RNA-seq, meta-RNA-seq, 16s rRNA gene sequencing with
10 | visualizations such as principal component analysis biplots (coloured using
11 | metadata for visualizing each variable), dendrograms and stacked bar plots,
12 | and effect plots (ALDEx2). Input is a table of counts and metadata file (if
13 | metadata exists), with options to filter data by count or by metadata to
14 | remove low counts, or to visualize select samples according to selected
15 | metadata.
16 | Imports:
17 | compositions,
18 | DT,
19 | grDevices,
20 | knitr,
21 | jsonlite,
22 | matrixStats,
23 | rmarkdown,
24 | shiny,
25 | stats,
26 | vegan,
27 | zCompositions
28 | VignetteBuilder: knitr
29 | Depends:
30 | R (>= 3.6),
31 | ALDEx2 (>= 1.18.0)
32 | License: MIT + file LICENSE
33 | LazyData: true
34 | Encoding: UTF-8
35 | RoxygenNote: 6.0.1
36 |
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/LICENSE:
--------------------------------------------------------------------------------
1 | Copyright (c) 2014, Daniel J Giguere, Jean Macklaim, Greg Gloor
2 |
3 | Permission is hereby granted, free of charge, to any person obtaining
4 | a copy of this software and associated documentation files (the
5 | "Software"), to deal in the Software without restriction, including
6 | without limitation the rights to use, copy, modify, merge, publish,
7 | distribute, sublicense, and/or sell copies of the Software, and to
8 | permit persons to whom the Software is furnished to do so, subject to
9 | the following conditions:
10 |
11 | The above copyright notice and this permission notice shall be
12 | included in all copies or substantial portions of the Software.
13 |
14 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
15 | EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
16 | MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
17 | NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
18 | LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
19 | OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
20 | WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFT
21 |
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/NAMESPACE:
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1 | exportPattern("^[^\\.]")
2 |
3 | import("knitr")
4 | import("rmarkdown")
5 | importFrom("jsonlite", "fromJSON")
6 | importFrom("stats", "dist")
7 | importFrom("vegan", "anosim", "adonis")
8 | importFrom("stats", "prcomp", "quantile", "dist")
9 | importFrom("grDevices", "rgb", "col2rgb", "colorRampPalette")
10 | importFrom("shiny", "validate", "need")
11 | importFrom("DT", "renderDataTable", "dataTableOutput")
12 |
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/R/internal.R:
--------------------------------------------------------------------------------
1 | #' Internal omicplotR functions.
2 | #'
3 | #' Internal functions for the app are not intended to be called by the
4 | #' user. Please refer to \link{omicplotr.run}.
5 | #'
6 | #' @author Daniel Giguere, Greg Gloor.
7 | #'
8 | #' @aliases omicplotr.anosim omicplotr.clr omicplotr.colvec omicplotr.filter
9 | #' omicplotr.colouredPCA omicplotr.getRemovedSamples
10 | #' omicplotr.getRemovedFeatures omicplotr.metadataFilter omicplotr.permanova
11 | #' omicplotr.report
12 | #'
13 | #' @export
14 | #'
15 | #' @examples
16 | #' # These functions are not meant to be called by the user. However, some
17 | #' # functions can be useful.
18 | #'
19 | #' data(otu_table)
20 | #' # Filter out your OTU table to remove rows that sum to less than 10.
21 | #'
22 | #' d <- omicplotr.filter(otu_table, min.reads = 10)
23 | #'
24 | #' @import ALDEx2
25 | #'
26 |
27 |
28 | omicplotr.anosim <- function(x, conds) {
29 | #get rid of tax column
30 | x$taxonomy <- NULL
31 |
32 | #replace zeros
33 | d <- zCompositions::cmultRepl(t(x), label = 0, method = "CZM")
34 |
35 | #calculate clr
36 | d.clr <- t(log(d) - rowMeans(log(d)))
37 |
38 | #dissimilarity matrix
39 | d.dist <- dist(d.clr)
40 |
41 | #calculate anosim, requires
42 | anosim(d.dist, conds, permutations = 999)
43 |
44 | #p-value of between conditions
45 | return(anosim$signif)
46 | }
47 |
48 | omicplotr.clr <- function(data, var.filt = 0, zero.method="CZM") {
49 |
50 | # replace zeros catch error if no 0 present
51 | if (any(data == 0)) {
52 |
53 | if (zero.method == "CZM") {
54 | data.0 <- zCompositions::cmultRepl(t(data), label = 0, method = "CZM")
55 | }
56 | if (zero.method == "pseudo") {
57 | data.0 <- t(data + 0.5)
58 | }
59 | } else {
60 | data.0 <- t(data)
61 | }
62 |
63 | # calculate CLR
64 | #x.clr <- t(apply(data.0, 1, function(x) {log(x) - mean(log(x))}))
65 |
66 | # calculate CLR
67 | x.clr <- as.matrix(log(data.0) - rowMeans(log(data.0)))
68 |
69 | # filter by variance
70 | if (var.filt == 0) {
71 | x.clr.var <- x.clr
72 | } else {
73 | # calculate variance
74 | var.clr <- matrixStats::colVars(x.clr)
75 |
76 | #replace names since colVars gets rid of them
77 | names(var.clr) <- colnames(x.clr)
78 |
79 | names.hvar <- names(var.clr)[which(var.clr > var.filt)]
80 | x.clr.var <- x.clr[, names.hvar]
81 | }
82 |
83 | # generate prcomp object
84 | x.pcx <- prcomp(x.clr.var)
85 | }
86 |
87 | omicplotr.colouredPCA <- function(data, colourvector, scale = 0, arrows = TRUE,
88 | taxonomy = NULL, show.taxonomy = FALSE, tax.level = 6, removenames = FALSE,
89 | names.cex = 1, points.cex = 0.8,
90 | main = "Principal Component Analysis Biplot") {
91 | x.var <- sum(data$sdev^2)
92 | PC1 <- paste("PC 1 Variance: %", round(sum(data$sdev[1]^2)/x.var *
93 | 100, 1))
94 | PC2 <- paste("PC 2 Variance: %", round(sum(data$sdev[2]^2)/x.var *
95 | 100, 1))
96 |
97 | points <- c(rep(".", length(dimnames(data$rotation)[[1]])))
98 | if ((isTRUE(show.taxonomy)) & (!is.null(taxonomy))) {
99 | genus <- vapply(strsplit(as.character(taxonomy), ";"), "[", tax.level, FUN.VALUE=character(1))
100 | }
101 |
102 | col = c("black", rgb(0, 0, 0, 0.4))
103 |
104 | # remove sample names
105 | if (isTRUE(removenames)) {
106 | xlabs <- c(rep(".", length(dimnames(data$x)[[1]])))
107 | names.cex = 5 * names.cex
108 | points.cex = points.cex
109 | } else {
110 | xlabs = unlist(dimnames(data$x)[1])
111 | names.cex = names.cex
112 | points.cex = points.cex
113 | }
114 |
115 | # if taxonomy is present, plot using taxonomies
116 | if (!isTRUE(show.taxonomy)) {
117 | points <- points
118 | } else {
119 | if (isTRUE(show.taxonomy)) {
120 | points <- genus
121 | } else {
122 | points <- points
123 | }
124 | }
125 |
126 | compositions::coloredBiplot(data, col = col, main = main, cex.main = 1.5,
127 | cex = c(names.cex, points.cex), xlabs.col = colourvector,
128 | var.axes = arrows, scale = scale, xlab = PC1, ylab = PC2,
129 | xlabs = xlabs, ylabs = points)
130 | }
131 |
132 |
133 | omicplotr.getRemovedFeatures <- function(x, x.clr) {
134 |
135 | # get rid of taxonomy column if it exists.
136 | x$taxonomy <- NULL
137 |
138 | # get original samples and retained samples
139 | otu.names <- rownames(x)
140 | otus <- dimnames(x.clr$rotation)[[1]]
141 |
142 | otu.missing <- c()
143 |
144 | # get missing samples
145 | otu.missing <- otu.names[!otu.names %in% otus]
146 |
147 | # samples that aren't na.
148 | otu.missing <- otu.missing[!is.na(otu.missing)]
149 |
150 | output <- x[otu.missing, ]
151 |
152 | # include OTUs as column because renderDataTable doesn't include
153 | # rownames
154 | output <- cbind(OTUs = rownames(output), output)
155 |
156 | return(output)
157 |
158 | }
159 |
160 |
161 | omicplotr.getRemovedSamples <- function(x, x.clr) {
162 |
163 | # get rid of taxonomy column if it exists
164 | x$taxonomy <- NULL
165 |
166 | # get original samples and retained samples
167 | names <- colnames(x)
168 | samples <- dimnames(x.clr$x)[[1]]
169 |
170 | missing <- c()
171 |
172 | # samples
173 | missing <- names[!names %in% samples]
174 |
175 | missing <- missing[!is.na(missing)]
176 |
177 | if (is.null(missing)) {
178 | output <- missing
179 | } else {
180 | output <- x[, missing]
181 |
182 | # work around for including rownames in dataTableOutput
183 | output <- cbind(OTUs = rownames(output), output)
184 | }
185 |
186 | return(output)
187 |
188 | }
189 |
190 | omicplotr.metadataFilter <- function(data, meta, column, values) {
191 |
192 | # order the metadata
193 | meta <- meta[order(rownames(meta)), ]
194 |
195 | # get rid of blank values
196 | s <- values[values != ""]
197 |
198 | # make list of samples
199 | meta.filt <- rownames(meta[which(meta[[column]] %in% s), ])
200 |
201 | # filter the data based on which samples remain in metadata
202 | x <- data[which(colnames(data) %in% meta.filt)]
203 |
204 | if (is.null(data$taxonomy)) {
205 | x <- x
206 | } else {
207 | x$taxonomy <- data$taxonomy
208 | }
209 |
210 | return(x)
211 | }
212 |
213 | omicplotr.permanova <- function(x, conds) {
214 |
215 | d.clr <- t(log(x) - rowMeans(log(x)))
216 |
217 | dist.clr <- dist(d.clr)
218 |
219 | conds <- data.frame(conds)
220 |
221 | colnames(conds) <- "grp"
222 |
223 | test <- adonis(dist.clr ~ grp, data = conds, method = "euclidean",
224 | permutations = 10000)
225 |
226 | return(test$`Pr(>F)`)
227 |
228 | }
229 |
230 |
231 |
232 | omicplotr.report <- function(x.all, feature = NULL) {
233 |
234 | features <- rownames(x.all)[which(abs(x.all$effect) > 1 & x.all$we.eBH <
235 | 0.1)]
236 |
237 | # effect sizes
238 | effect <- x.all$effect[which(abs(x.all$effect) > 1 & x.all$we.eBH <
239 | 0.1)]
240 |
241 | # diff btw and diff win
242 | diff.btw <- x.all$diff.btw[which(abs(x.all$effect) > 1 & x.all$we.eBH <
243 | 0.1)]
244 | diff.win <- x.all$diff.win[which(abs(x.all$effect) > 1 & x.all$we.eBH <
245 | 0.1)]
246 |
247 | # table of of significantly different OTUs with BH fdr < 0.1.
248 | sig.output <- cbind(features, effect, diff.btw, diff.win)
249 |
250 | }
251 |
252 |
253 |
254 | omicplotr.filter <- function(data, min.reads = 0, min.count = 0, min.sum = 0,
255 | min.prop = 0, max.prop = 1) {
256 |
257 | if (is.null(data$taxonomy)) {
258 | taxCheck <- TRUE
259 | } else {
260 | taxCheck <- FALSE
261 | }
262 |
263 | if (isTRUE(taxCheck)) {
264 | # order for colouring
265 | # make a matrix for vectorization
266 | x <- as.matrix(data[order(colnames(data))])
267 |
268 | # filter by min reads per sample
269 | data.0 <- x[, which(colSums(x) > min.reads)]
270 |
271 | # filter by min count per feature
272 | data.1 <- data.0[which(matrixStats::rowMaxs(data.0) >= min.count), ]
273 |
274 | # filter by sum of count per feature
275 | data.2 <- data.1[which(rowSums(data.1) >= min.sum), ]
276 |
277 | # calculate proportions
278 | d.frac <- t(t(data.2)/colSums(data.2))
279 |
280 | # filter by proportions, back to dataframe
281 | x.filt <- as.data.frame(data.2[which((matrixStats::rowMaxs(d.frac) > min.prop) & (matrixStats::rowMaxs(d.frac) < max.prop)),])
282 |
283 | } else {
284 | # order for colouring
285 | tax <- data$taxonomy
286 | x <- data[order(colnames(data[seq_len(length(data) - 1)]))]
287 |
288 | # filter by min reads per sample
289 | data.0 <- as.matrix(x[, which(colSums(x[, seq_along(x)]) >= min.reads)])
290 |
291 | # since tax and data.0 are in the same order, separate, convert to matrix, and remove rows in both tax and data.0 that have max counts less than expected.
292 |
293 | # filter by min count per feature, do the same for the tax
294 | data.1 <- data.0[which(matrixStats::rowMaxs(data.0) >= min.count), ]
295 | tax.1 <- tax[which(matrixStats::rowMaxs(data.0) >= min.count)]
296 |
297 | # filter by sum of count per feature
298 | data.2 <- data.1[which(rowSums(data.1) >= min.sum),]
299 | tax.2 <- tax.1[which(rowSums(data.1) >= min.sum)]
300 |
301 | # calculate proportions
302 | d.frac <- t(t(data.2)/colSums(data.2))
303 |
304 | # filter by proportions
305 | x.filt <- as.data.frame(data.2[which((matrixStats::rowMaxs(d.frac) > min.prop) & (matrixStats::rowMaxs(d.frac) < max.prop)),])
306 | tax.filt <- as.data.frame(tax.2[which((matrixStats::rowMaxs(d.frac) > min.prop) & (matrixStats::rowMaxs(d.frac) < max.prop))])
307 |
308 | colnames(tax.filt) <- "taxonomy"
309 |
310 | x.filt <- cbind(x.filt, tax.filt)
311 |
312 | }
313 | return(x.filt)
314 | }
315 |
316 |
317 | omicplotr.colvec <- function(data, meta, opacity = 1, column, type = 3) {
318 |
319 | df <- as.data.frame(unlist(dimnames(data$x)[1]))
320 |
321 | colnames(df) <- "samples"
322 | # add empty column (which is gonna be the ample list for colouring)
323 | df$correct <- NA
324 | # introduces NA where metadata is not present for sample the important
325 | # thing is that this keeps the order of the data
326 | for (i in seq_along(df$samples)) {
327 | if (df$samples[i] %in% rownames(meta)) {
328 | df$correct[i] <- as.character(df$samples[i])
329 | } else {
330 | df$correct[i] <- NA
331 | }
332 | }
333 |
334 | # colour column
335 | df$colour <- NA
336 |
337 | # if correct != present, colour black. this means metadata was missing
338 | # for data point
339 | df$colour[is.na(df$correct)] <- "black"
340 |
341 | # get unique features of columns in metadata
342 | u <- unique(meta[[column]])
343 | # get rid of NAs
344 | u <- u[!is.na(u)]
345 |
346 | # default colour palette
347 | colours <- c("indianred1", "steelblue3", "skyblue1", "mediumorchid",
348 | "royalblue4", "olivedrab3", "pink", "#FFED6F", "mediumorchid3",
349 | "ivory2")
350 |
351 | # colour the colour column for up to ten colours
352 | idx = match(meta[column][df$correct,], as.character(u))
353 | df$colour = colours[idx]
354 | df$colour[is.na(df$colour)] = "black"
355 |
356 | # different colouringtype
357 | if (type == 1) {
358 |
359 | # TODO get rid of this if using command line
360 | validate(need(is.integer(meta[[column]]), "Nonnumeric
361 | data detected. Please click 'Nonnumeric metadata'"))
362 |
363 | # get rid of old column made
364 | df$colour <- NULL
365 |
366 | # make age column
367 | df$age <- NA
368 |
369 | # get the age of each sample
370 | for (i in seq_along(df$correct)) {
371 | if (is.na(meta[column][df$correct[i], ])) {
372 | df$age[i] <- NA
373 | } else {
374 | df$age[i] <- meta[column][df$correct[i], ]
375 | }
376 | }
377 |
378 | # order data frame in order
379 | df.sort <- df[order(df$age), ]
380 |
381 | df.sort$col <- NA
382 |
383 | # colour each unique number seperately
384 | df.u <- unique(df.sort$age)
385 |
386 | len <- length(df.u)
387 |
388 | # generate colour function
389 | c.hex <- colorRampPalette(c("red", "blue"))(len)
390 |
391 | #convert colour value to rgb, get alpha input from opacity, convert
392 | #back to hex
393 |
394 | new.cols <- c()
395 |
396 | for (i in seq_along(c.hex)) {
397 | #get colour
398 | col <- c.hex[i]
399 |
400 | #convert to rgb
401 | new.col <- col2rgb(col, alpha=TRUE)
402 |
403 | #replace alpha with sliderInput
404 | #convert colour with new opacity to hex
405 | col.fin <- rgb(new.col["red",1], new.col["green",1], new.col["blue",1], (opacity*255), maxColorValue=255)
406 |
407 | new.cols <- c(new.cols, col.fin)
408 | }
409 |
410 | # colour each unique age
411 | for (i in seq_along(df.sort$age)) {
412 | df.sort$col[df.sort$age == df.u[i]] <- new.cols[i]
413 | }
414 |
415 | # colour the NAs black. these are missing data points.
416 | for (i in seq_along(df.sort$age)) {
417 | if (is.na(df.sort$col[i])) {
418 | df.sort$col[i] <- rgb(0,0,0,opacity)
419 | }
420 | }
421 |
422 | # reorder the df by sample now so it matches the data
423 | df.sort <- df.sort[order(df.sort$samples), ]
424 |
425 | # voila, c'est le colour!
426 | sorted <- c()
427 | sorted$col <- df.sort$col
428 |
429 | } else if (type == 2) {
430 |
431 | validate(need(is.integer(meta[[column]]), "Nonnumeric
432 | data detected. Please click 'Nonnumeric metadata'"))
433 |
434 | # quartile
435 | df$colour <- NULL
436 |
437 | # make age column
438 | df$age <- NA
439 |
440 | # get the age of each sample
441 | for (i in seq_along(df$correct)) {
442 | if (is.na(meta[column][df$correct[i], ])) {
443 | df$age[i] <- NA
444 | } else {
445 | df$age[i] <- meta[column][df$correct[i], ]
446 | }
447 | }
448 |
449 | df$col <- NA
450 |
451 | c <- colorRampPalette(c("red", "blue"))(4)
452 |
453 | #convert into rgb
454 |
455 | c.rgb <- col2rgb(c, alpha = TRUE)
456 |
457 | #convert back to hex with new alpha
458 | new.cols <- c()
459 |
460 | for (i in seq(dim(c.rgb)[2])) {
461 | #get colour as rgb
462 | c.rgb.1 <- c.rgb[,i]
463 |
464 | #replace alpha with sliderInput
465 | #convert colour with new opacity to hex
466 | col.fin <- rgb(c.rgb.1["red"], c.rgb.1["green"], c.rgb.1["blue"], (opacity*255), maxColorValue=255)
467 |
468 | new.cols <- c(new.cols, col.fin)
469 | }
470 |
471 | # make quartile rank column
472 | sorted <- within(df, col <- as.integer(cut(df$age, quantile(df$age,
473 | na.rm = TRUE), include.lowest = TRUE)))
474 |
475 | sorted$col <- new.cols[sorted$col]
476 |
477 | # replace any NAs with black
478 | sorted$col[is.na(sorted$col)] <- rgb(0,0,0,opacity)
479 |
480 | } else if (type == 3) {
481 | sorted <- c()
482 |
483 | c.rgb <- col2rgb(df$colour, alpha = TRUE)
484 |
485 | #convert back to hex with new alpha
486 | new.cols <- c()
487 |
488 | for (i in seq(dim(c.rgb)[2])) {
489 | #get colour as rgb
490 | c.rgb.1 <- c.rgb[,i]
491 |
492 | #replace alpha with sliderInput
493 | #convert colour with new opacity to hex
494 | col.fin <- rgb(c.rgb.1["red"], c.rgb.1["green"], c.rgb.1["blue"], (opacity*255), maxColorValue=255)
495 |
496 | new.cols <- c(new.cols, col.fin)
497 | }
498 |
499 | sorted$col <- new.cols
500 | } else {
501 | return("")
502 | }
503 | return(sorted$col)
504 | }
505 |
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/R/metadata.r:
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1 | #' Vaginal microbiome OTU table metadata
2 | #'
3 | #' Associated metadata to \code{\link{otu_table}}.
4 | #'
5 | #' @name metadata
6 | #'
7 | #' @docType data
8 | #'
9 | #' @usage data(metadata)
10 | #'
11 | #' @references Macklaim et al (2014). Microb Ecol Health Dis.
12 | #' doi: http://dx.doi.org/10.3402/mehd.v26.27799
13 | #'
14 | #' @format A data frame with 297 rows and 35 columns, where rows are samples
15 | #' and columns are collected metadata.
16 | #'
17 | #' @seealso \code{\link{otu_table}}
18 | #'
19 | NULL
20 |
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/R/omicplotr.R:
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1 | #' \code{omicplotR}
2 | #'
3 | #' A Shiny app for visual exploration of omic datasets as
4 | #' compositions, and differential abundance analysis using ALDEx2. Useful for
5 | #' exploring RNA-seq, meta-RNA-seq, 16s rRNA gene sequencing and more with
6 | #' visualizations such as principal component analysis biplot (coloured using
7 | #' metadata for visualizing each variable), association plots (igraph),
8 | #' dendrograms and stacked bar plots, and effect plots (ALDEx2). Input is a
9 | #' table of counts and metadata file (if metadata exists), with options to
10 | #' filter data by count or by metadata to remove low counts, or to visualize
11 | #' select samples according to selected metadata. The Shiny app's graphical
12 | #' user interface facilitates visual exploration for new and experienced
13 | #' users of R alike.
14 | #'
15 | #' @details To launch the \code{shiny} app in your default browser, type
16 | #' \code{omicplotr.run()}.
17 | #'
18 | #' @author Daniel Giguere, Jean Macklaim, Greg Gloor
19 | #'
20 | #' @seealso \code{\link{omicplotr.run}}
21 | #'
22 | "_PACKAGE"
23 |
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/R/omicplotr.run.r:
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1 | #' Run \code{omicplotR} \code{Shiny} app.
2 | #'
3 | #' Launches \code{Shiny} for \code{omicplotR} in default browser. This
4 | #' graphical user interface facilitates visual exploration of datasets for
5 | #' both new and experienced R users alike.
6 | #'
7 | #' @author Daniel Giguere
8 | #'
9 | #' @export
10 | #'
11 | #' @examples
12 | #' # To run omicplotR, use `omicplotr.run()` function. This will open the shiny
13 | #' # app in your default browser.
14 | #'
15 | #' # omicplotr.run()
16 | #'
17 | #' # After running omicplotr.run(), you can filter your data and make a PCA
18 | #' # biplot. Internal functions are not intended to be called by the user.
19 | #'
20 | #' data(otu_table)
21 | #' d.filt <- omicplotr.filter(otu_table)
22 | #'
23 | #' @value
24 | #' Will launch the Shiny App. There is no value.
25 | #'
26 | #' @import ALDEx2
27 | #'
28 |
29 | omicplotr.run <- function() {
30 |
31 | appDir <- system.file("shiny-app", package = "omicplotR")
32 | if (appDir == "") {
33 | stop("Could not find directory. Try reinstalling omicplotR", call = FALSE)
34 | }
35 |
36 | shiny::runApp(appDir)
37 | }
38 |
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/R/otu_table.r:
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1 | #' Vaginal microbiome OTU table
2 | #'
3 | #' This dataset contains a count table of operational taxonomic units (OTUs)
4 | #' from a 16s rRNA gene sequencing experiment characterising changes in
5 | #' bacterial microbiota from oral antimicrobial or probiotic treatments.
6 | #' Associated metadata is contained in \code{\link{metadata}}.
7 | #'
8 | #' @name otu_table
9 | #'
10 | #' @usage data(otu_table)
11 | #'
12 | #' @docType data
13 | #'
14 | #' @references Macklaim et al (2014). Microb Ecol Health Dis.
15 | #' doi: http://dx.doi.org/10.3402/mehd.v26.27799
16 | #'
17 | #' @format A data frame with 77 rows and 298 columns. The last column contains
18 | #' taxonomic information for each OTU. Samples are columns, OTUs are rows.
19 | #'
20 | NULL
21 |
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/README.md:
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1 | # omicplotR
2 | An R package to visualize high-throughput sequencing data. Click on the wiki for more!
3 | [](https://zenodo.org/badge/latestdoi/101769044)
4 |
5 | Read more about omicplotR here:
6 |
7 | > [__Giguere, DJ, Macklaim, JM, Lieng, BY, Gloor, GB.__ omicplotR: visualizing omic datasets as compositions. BMC Bioinformatics 20, 580 (2019)](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3174-x)
8 |
9 | # Table of content
10 |
11 | * [Introduction](#introduction)
12 | * [Installation](#installation)
13 | * [Quick usage](#quick-usage)
14 | * [Submit bug report](#submit-bug-report)
15 |
16 | ## Introduction
17 |
18 | As input, omicplotR takes the following:
19 | * A data file and optionally a metadata file
20 | * The data file is a count table of sequencing reads with samples as columns and features by rows
21 | * An additional column of taxonomic identifiers may be included. Column name must be 'taxonomy', identifiers must contain at least 4 levels separated by a semi-colon (Bacteria;Firmicutes;Bacilli;Lactobacillales)
22 |
23 | Here is an example of how your data file should look:
24 |

25 |
26 | * The metadata file must contain samples by rows and identifiers by columns
27 |
28 | Here is an example of how your metadata should look like:
29 |
30 | 
31 |
32 | Reasons to use omicplotR:
33 | * It allows you to explore your raw sequencing count data without coding in R
34 | * It performs interactive filtering
35 | * It allows you to easily colour PCA biplots according to metadata
36 | * It generates interactive effect plots
37 | * It allows easy download of publically available data from the EBI MGnify portal
38 |
39 | Reasons to **not** use omicplotR:
40 | * You have thousands of samples and tens of thousands of features (it will be quicker using the command line)
41 |
42 | ## Installation
43 |
44 | The first thing to check is if you have the current version of [Bioconductor](http://bioconductor.org). Look at the `BiocManager` [vignette](https://cran.r-project.org/web/packages/BiocManager/vignettes/BiocManager.html) for instructions on installing or upgrading to 3.10.
45 |
46 | You can check the version of Bioconductor that is install if you already have `BiocManager` installed.
47 |
48 | ```
49 | BiocManager::version()
50 | ```
51 |
52 | Once you have ensured that you have the correct version of Bioconductor, install `omicplotR`:
53 |
54 | ```
55 | BiocManager::install("omicplotR")
56 | ```
57 |
58 | The development version can be installed directly from Github:
59 |
60 | ```
61 | install.packages("devtools")
62 | devtools::install_github("dgiguer/omicplotR")
63 | ```
64 |
65 | ## Quick usage
66 |
67 | The quickest way to run `omicplotR` is:
68 |
69 | ```
70 | library(omicplotR)
71 | omicplotr.run()
72 | ```
73 |
74 | This will pop up a window in your default browser.
75 |
76 | To view the tutorials, visit [the wiki](https://github.com/dgiguer/omicplotR/wiki).
77 |
78 | ## Submit bug report
79 |
80 | If omicplotR is not working as expected, please submit an issue that includes the following information. This will help me help you!
81 |
82 | ```
83 | Please make sure to fill in this template when submitting an issue. Thank you for taking the time to submit an issue!
84 | - [x] Please check off boxes below like this.
85 |
86 | What is the error message that appears in the R console?
87 |
88 | - [ ] Check that you are using the newest release of R.
89 | - [ ] Check that you are using the newest release of omicplotR.
90 |
91 | What OS are you on?
92 |
93 | - [ ] Windows
94 | - [ ] macOS
95 | - [ ] Linux
96 |
97 | What version of your OS are you on?
98 |
99 | What is the expected behaviour?
100 |
101 | What is the actual behaviour?
102 |
103 | What does the error look like? (submit screenshot of browser if possible)
104 | ```
105 |
106 |
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/data/metadata.rda:
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https://raw.githubusercontent.com/dgiguer/omicplotR/21191113186150b0286457da4a015d780dba8eff/data/metadata.rda
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/data/otu_table.rda:
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https://raw.githubusercontent.com/dgiguer/omicplotR/21191113186150b0286457da4a015d780dba8eff/data/otu_table.rda
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/inst/.DS_Store:
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https://raw.githubusercontent.com/dgiguer/omicplotR/21191113186150b0286457da4a015d780dba8eff/inst/.DS_Store
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/inst/NEWS:
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1 | CHANGES IN VERSION 1.7.1
2 | --------------------------
3 | - bug fix to cause by Shiny 1.4.0 (renderDataTable causes error in jquery). solution is to import DT package and specify DT::renderDataTable and DT::dataTableOutput.
4 | - ensured that ALDEx2 dependency for aldex.plot feature is correctly implemented
5 | - added Brandon Lieng as author
6 |
7 | CHANGES IN VERSION 1.7.0
8 | --------------------------
9 | - bioconductor dev version 3.11, no changes since 1.5.4
10 |
11 | CHANGES IN VERSION 1.5.4
12 | --------------------------
13 | - explicitly calling some functions to prevent conflicts (jsonlite::fromJSON)
14 | - corrected namespace and description
15 | - removed "require(libraries") from ui.
16 | - bug fix for calculating aldex object. sometimes would need to click generate effect plot twice.
17 | - version bump
18 | - changed T to TRUE in rab_script and server.R
19 |
20 |
21 | CHANGES IN VERSION 1.5.1
22 | --------------------------
23 | - choice of pseudocount or CZM
24 | - changed how conditions are selected manually for effect size. now, you input the column number
25 | - added ability to download GO slim annotated feature tables directly from MGNify database by inputting a Study ID
26 | - added density plots for interactive effect sizes
27 | - currently depends on specific version of ALDEx2 (temporary)
28 |
29 |
30 | CHANGES IN VERSION 1.1.2
31 | --------------------------
32 | - bug fix for CZM in RAB plots. if not zeros, plots would fail.
33 |
34 |
35 | CHANGES IN VERSION 1.1.2
36 | --------------------------
37 | - updated install instructions to use `BiocManager`
38 |
39 |
40 | CHANGES IN VERSION 1.1.1
41 | --------------------------
42 | - added slider inputs to change size and opacity of sample names for biplot and coloured biplot
43 | - changed UI for filtering page
44 | - added downloadable scripts for PCA biplots, dendrogram/barplots, and effect plots (simple effect plot script).
45 |
46 |
47 | CHANGES IN VERSION 0.99.4
48 | --------------------------
49 |
50 | - changed vignette to html instead of pdf.
51 | - edited vignette.
52 |
53 | CHANGES IN VERSION 0.99.3
54 | --------------------------
55 |
56 | - bug fix. extrainformation.rmd changed to extrainformation.Rmd.
57 |
58 |
59 | CHANGES IN VERSION 0.99.0
60 | --------------------------
61 |
62 | - release version.
63 |
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/inst/shiny-app/PCA_script.R:
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1 | #script for reproducing the PCA plot. values chosen for filtering in omicplotR are listed above
2 | #subsetting by metadata is intended for coloured biplots so it isn't included here
3 | #all omicplotr functions can be found in inst/shiny-app/internal.r
4 |
5 | library(zCompositions)
6 | library(ALDEx2)
7 | library(omicplotR)
8 |
9 | ##################################################################
10 | # #
11 | # You must change the file variable to your own file name #
12 | # #
13 | # #
14 | ##################################################################
15 | #change filename.txt to your filename, make sure it follow input requirements
16 | file <- "filename.txt"
17 |
18 | #read file
19 | data <- read.table(
20 | file,
21 | header = TRUE,
22 | sep = "\t",
23 | stringsAsFactors = FALSE,
24 | quote = "",
25 | row.names = 1,
26 | check.names = FALSE,
27 | comment.char = "",
28 | na.strings = "")
29 |
30 | #filter data
31 | x.filt <- omicplotr.filter(data, min.reads = min.reads, min.count = min.count, min.prop = min.prop, max.prop = max.prop, min.sum = min.sum)
32 |
33 | #check for taxonomy column
34 | if (is.null(data$taxonomy)) {
35 | taxCheck <- TRUE
36 | } else {
37 | taxCheck <- FALSE
38 | }
39 |
40 | if (isTRUE(taxCheck)) {
41 | x.filt <- x.filt
42 | } else {
43 | x.filt$taxonomy <- NULL
44 | }
45 |
46 | #calculates clr and generates prcomp object
47 | data.pr <- omicplotr.clr(x.filt, var.filt)
48 |
49 | #calculate variance for x/y axis of plot
50 | x.var <- sum(data.pr$sdev ^ 2)
51 | PC1 <- paste("PC 1 Variance: %", round(sum(data.pr$sdev[1] ^ 2) / x.var * 100, 1))
52 | PC2 <- paste("PC 2 Variance: %", round(sum(data.pr$sdev[2] ^ 2) / x.var*100, 1))
53 |
54 | ##############################################################################
55 |
56 | #checks for biplot
57 |
58 | #take taxonomy column from data if it exists
59 | taxonomy <- x.filt$taxonomy
60 |
61 | #if Show taxonomy checkbox is clicked, take chosen level or genus by default
62 | if (isTRUE(taxoncheck)) {
63 | taxselect <- as.numeric(input$taxlevel)
64 | } else {
65 | taxselect <- 6
66 | }
67 |
68 | #get genus (or other level)
69 | genus <- vapply(strsplit(as.character(taxonomy), "[[:punct:]]"), "[", taxselect, FUN.VALUE=character(1))
70 |
71 | #do checks for arrows
72 | if (isTRUE(arrowcheck)) {
73 | arrows = FALSE
74 | } else {
75 | arrows = TRUE
76 | }
77 | #if taxonomy is is null, use periods as points for features.
78 | #if taxoncheckbox is checked, show genus instead of points
79 | if (isTRUE(taxoncheck)) {
80 | points <- genus
81 | } else {
82 | points <- c(rep(".", length(dimnames(data.pr$rotation)[[1]])))
83 | }
84 |
85 | #remove sample names if checkbox clicked
86 | if (isTRUE(removenames)) {
87 | xlabs <- c(rep(".", length(dimnames(data.pr$x)[[1]])))
88 | size = c(5, 0.8)
89 | } else {
90 | xlabs = unlist(dimnames(data.pr$x)[1])
91 | size = c(1.0, 0.8)
92 | }
93 |
94 | ##############################################################################
95 |
96 | #colour of points (features black, samples red)
97 | col = c("black", rgb(0, 0, 0, 0.2))
98 |
99 | #add or change options for biplot.
100 | biplot(
101 | data.pr,
102 | main = "Principal Component Analysis",
103 | cex.main = 1.5,
104 | cex = size,
105 | col = col,
106 | scale = scale.slider,
107 | var.axes = arrows,
108 | xlab = PC1,
109 | ylab = PC2,
110 | xlabs = xlabs,
111 | ylabs = points
112 | )
113 |
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/inst/shiny-app/effect_script.R:
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1 | #script for reproducing the effect plots. values chosen for filtering in omicplotR are listed above
2 |
3 | library(ALDEx2)
4 | library(omicplotR)
5 |
6 | ##################################################################
7 | # #
8 | # You must change the file variable to your own file name #
9 | # and set conditions to calculate ALDEx2 #
10 | # #
11 | ##################################################################
12 | #change filename.txt to your filename, make sure it follow input requirements
13 | file <- "filename.txt"
14 |
15 | #set which columns correspond to what conditions conditions.
16 | #your columns must be ordered according to these conditions (view wiki).
17 | #i.e., first three columns are time 0, last three columns are time 1.
18 | #these conditions are for the selex dataset
19 | conds <- c(rep("0", 7), rep("1", 7))
20 |
21 | #read file
22 | data <- read.table(
23 | file,
24 | header = TRUE,
25 | sep = "\t",
26 | stringsAsFactors = FALSE,
27 | quote = "",
28 | row.names = 1,
29 | check.names = FALSE,
30 | comment.char = "",
31 | na.strings = "")
32 |
33 | #filter data
34 | x.filt <- omicplotr.filter(data, min.reads = min.reads, min.count = min.count, min.prop = min.prop, max.prop = max.prop, min.sum = min.sum)
35 |
36 | #check for taxonomy column
37 | if (is.null(data$taxonomy)) {
38 | taxCheck <- TRUE
39 | } else {
40 | taxCheck <- FALSE
41 | }
42 |
43 | #get rid of taxonomy column if present
44 | if (isTRUE(taxCheck)) {
45 | x.filt <- x.filt
46 | } else {
47 | x.filt$taxonomy <- NULL
48 | }
49 |
50 | #use ALDEx2 to for differential abundance analysis
51 | #change MC or denominator if desired. More (1000-2000) MC samples is
52 | # recommended, but takes longer to calculate.
53 | d.clr <- aldex.clr(x.filt, mc.samples=128, conds = conds, denom = "all", verbose=TRUE)
54 |
55 | #effect plot
56 | aldex.plot(d.clr, type="MW", test="welch", all.cex = 1.5, rare.cex = 1.5, called.cex = 1.5, xlab = "Dispersion", ylab = "Difference")
57 | title(main = "Effect Plot")
58 |
59 | #Bland-Altman plot
60 | aldex.plot(d.clr, type="MA", test="welch", all.cex = 1.5, rare.cex = 1.5, called.cex = 1.5, xlab = "CLR abundance", ylab = "Difference")
61 | title(main = "Bland-Altman Plot")
62 |
63 | ######### save both in one pdf
64 | # pdf("omicplotR_effect.pdf", width = 10)
65 | # par(mfrow=c(1,2))
66 | # aldex.plot(d.clr, type="MW", test="welch", all.cex = 1.5, rare.cex = 1.5, called.cex = 1.5, xlab = "Dispersion", ylab = "Difference")
67 | # title(main = "Effect Plot")
68 | # #Bland-Altman plot
69 | # aldex.plot(d.clr, type="MA", test="welch", all.cex = 1.5, rare.cex = 1.5, called.cex = 1.5, xlab = "CLR abundance", ylab = "Difference")
70 | # title(main = "Bland-Altman Plot")
71 | # dev.off()
72 | #########
73 |
74 |
75 |
76 |
77 |
78 |
79 |
80 |
81 |
82 |
83 |
84 |
85 |
86 |
87 |
88 |
89 |
90 |
91 |
92 |
93 |
94 | a
95 |
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/inst/shiny-app/example_data.txt:
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1 | #OTU ID 226bbv 35bcont 261bbv 21bcont 138bvvc 180bvvc 53bcont 94bvvc 298bbv 19bcont 188bvvc 284bbv 246bbv 92bvvc 76bvvc 305bbv 165bvvc 311bbv 319bbv 178bvvc 66bvvc 31bcont 173bvvc 219bbv 172bvvc 233bbv 132bvvc 67bvvc 198bvvc 228bbv 251bbv 133bvvc 36bcont 93bvvc 177bvvc 73bvvc 205bbv 202bbv 276bbv 95bvvc 107bvvc 50bcont 273bbv 23bcont 239bbv 28bcont 274bbv 24bcont 150bvvc 26bcont 79bvvc 212bbv 42bcont 253bbv 63bcont 199bvvc 280bbv 160bvvc 51bcont 250bbv 323bbv 120bvvc 148bvvc 314bbv 110bvvc 235bbv 39bcont 209bbv 269bbv 27bcont 136bvvc 109bvvc 142bvvc 229bbv 200bvvc 56bcont 171bvvc 146bvvc 186bvvc 83bvvc 85bvvc 268bbv 96bvvc 324bbv 55bcont 78bvvc 87bvvc 7bcont 70bvvc 65bvvc 255bbv 12bcont 245bbv 302bbv 317bbv 176bvvc 265bbv 320bbv 5bcont 121bvvc 191bvvc 68bvvc 168bvvc 170bvvc 206bbv 101bvvc 318bbv 82bvvc 48bcont 225bbv 135bvvc 166bvvc 71bvvc 105bvvc 33bcont 260bbv 37bcont 60bcont 123bvvc 309bbv 306bbv 299bbv 29bcont 98bvvc 17bcont 43bcont 222bbv 195bvvc 190bvvc 16bcont 102bvvc 179bvvc 315bbv 128bvvc 147bvvc 18bcont 157bvvc 287bbv 272bbv 145bvvc 221bbv 241bbv 112bvvc 41bcont 30bcont 249bbv 328bbv 296bbv 119bvvc 288bbv 20bcont 325bbv 293bbv 13bcont 46bcont 116bvvc 141bvvc 15bcont 283bbv 3bcont 204bbv 153bvvc 97bvvc 52bcont 62bcont 257bbv 326bbv 104bvvc 25bcont 126bvvc 156bvvc 162bvvc 266bbv 58bcont 327bbv 175bvvc 44bcont 310bbv 227bbv 184bvvc 14bcont 4bcont 254bbv 2bcont 64bcont 275bbv 292bbv 203bbv 106bvvc 74bvvc 139bvvc 291bbv 301bbv 127bvvc 321bbv 308bbv 6bcont 54bcont 264bbv 201bbv 224bbv 187bvvc 84bvvc 234bbv 277bbv 40bcont 100bvvc 89bvvc 300bbv 223bbv 159bvvc 8bcont 137bvvc 111bvvc 244bbv 99bvvc 270bbv 114bvvc 278bbv 211bbv 164bvvc 125bvvc 240bbv 294bbv 207bbv 161bvvc 108bvvc 316bbv 237bbv 118bvvc 75bvvc 80bvvc 313bbv 140bvvc 196bvvc 248bbv 124bvvc 197bvvc 115bvvc 289bbv 72bvvc 304bbv 45bcont 238bbv 163bvvc 122bvvc 77bvvc 189bvvc 192bvvc 144bvvc 143bvvc 11bcont 242bbv 286bbv 81bvvc 307bbv 117bvvc 271bbv 282bbv 256bbv 281bbv 230bbv 279bbv 130bvvc 208bbv 59bcont 9bcont 210bbv 232bbv 86bvvc 267bbv 10bcont 103bvvc 297bbv 49bcont 129bvvc 155bvvc 182bvvc 169bvvc 214bbv 131bvvc 34bcont 154bvvc 57bcont 174bvvc 90bvvc 149bvvc 181bvvc 259bbv 290bbv 158bvvc 231bbv 213bbv 152bvvc 243bbv 91bvvc 312bbv taxonomy
2 | 0 2003 1814 654 19424 4419 16789 8617 32673 1605 5833 62893 21914 8515 7239 44804 1826 3380 1374 992 39283 78271 2509 3887 942 29947 1517 12654 3810 11731 1390 697 2655 34585 3681 33826 6701 1791 3982 16883 5547 9108 9474 2159 4051 9564 22248 6058 5714 3924 4216 22866 4525 5051 473 17558 9296 2763 30569 6047 2108 1531 27997 4309 11271 57249 658 2973 14860 1693 2531 39180 5490 18434 3233 12751 83208 23087 19382 27486 5767 25654 4510 72762 14936 6038 4360 54633 17079 18760 62885 920 5419 1165 4218 13044 7305 3207 1496 2520 33604 29835 45695 52476 10557 3171 5283 11491 8125 32878 5236 18682 3390 26528 57630 6572 10553 3611 8950 4248 818 1238 826 2132 60050 40649 1722 6518 29197 4582 4851 6903 4188 1069 20060 4207 11620 12140 2189 15026 22884 1149 1244 62343 17198 2496 9774 3482 12441 30232 29436 12129 627 1227 2066 2060 65122 11279 6352 1182 8292 22869 4635 50254 6406 7279 1141 11645 9954 45291 35857 19399 16127 18663 62811 7021 4933 41394 890 752 24200 4928 3617 836 52375 14150 2675 1250 22828 28775 7103 2732 1148 2475 40444 2051 1851 10822 55173 2297 8622 11220 14957 26775 1596 1084 4865 7665 7094 1778 933 26412 29053 6544 42794 2099 7297 2692 7729 23702 1822 43882 39884 1836 17662 3448 51527 63698 2804 726 7694 37864 22473 5330 7304 33521 1022 4750 15323 36600 1682 9848 25884 7949 700 34504 59178 3565 10241 32262 7602 5080 14186 13079 3772 12412 1069 72793 4172 1840 1323 2882 1067 2281 31244 20263 9230 34806 2999 12380 21978 3567 21480 7088 1267 48001 15070 3035 5495 13665 2318 11757 9084 6958 7452 4685 4697 3543 3088 479 1780 29276 1157 2343 7692 877 2921 1897 Bacteria;Firmicutes;Bacilli;Lactobacillales;Lactobacillaceae;Lactobacillus;iners
3 | 1 4392 1081 269 2428 31495 4093 5742 3046 265 1591 9757 219 318 26522 3646 371 36756 460 443 2223 5151 2045 4082 333 4369 442 3247 2389 14427 484 260 960 7007 14450 1377 36779 416 873 472 3056 2508 5582 133 23906 3556 1945 189 51364 28555 28214 3214 853 2074 96 2232 22948 195 1758 3472 224 278 57331 34394 456 1881 218 815 1319 443 1191 1215 1160 3013 196 11901 188268 2673 21906 3915 2145 1280 480 4551 464 29900 25467 1448 21574 33167 4873 149 25503 351 186 458 34746 210 710 3592 7559 3782 3433 6335 30198 664 60235 378 1909 2745 200 1365 41171 37055 1506 614 191 2269 57576 9909 395 432 278 23277 4488 3079 4409 604 7794 39087 1417 3653 2449 278 4994 25105 12465 1371 451 814 4413 579 233 1823 28283 18263 134 9408 992 3798 681 2106 118 490 15668 10263 2750 2317 19011 201 31336 1508 11208 2928 15799 2477 330 198 6664 1381 11425 15568 35106 396 3004 7848 28288 1126 473 308 12393 1609 6500 123 3438 5658 238 467 866 2493 35200 17367 280 109 3134 154 240 3149 4707 524 480 729 1735 3460 593 107 743 4494 3060 576 567 2007 5438 30411 1892 8261 2755 370 57469 143 696 2850 6938 15249 404 631 9796 4241 530 423 3970 2045 5127 280 23522 1576 526 44040 14616 2873 306 14413 173 1355 457 1923 4868 39514 2943 5618 4475 24109 26510 336 398 1129 215 3166 447 447 106 337 218 141 1758 647 3317 1233 1319 196 12825 240 1958 4316 144 3824 1073 18400 33050 35879 1271 1965 1244 24822 1881 3357 3300 28153 19267 160 7587 2045 196 1153 6888 208 21811 692 Bacteria;Firmicutes;Bacilli;Lactobacillales;Lactobacillaceae;Lactobacillus;crispatus
4 | 2 886 6379 5286 1926 1840 19684 6447 2135 1611 2407 783 922 814 949 1233 9216 409 1931 7646 1488 7600 5673 16098 6921 1005 5726 4100 15119 1011 4871 6340 5013 759 913 979 2486 11065 24850 5027 47377 52422 46954 7367 1510 949 423 6520 1198 483 704 2382 6898 803 964 1344 2541 2369 24766 38684 1402 1997 3609 539 8471 3841 913 444 9563 11842 13735 1168 31945 6602 925 1825 2177 1911 1028 1721 7122 1518 5010 4986 734 16676 1049 1231 1734 2387 2532 2373 5207 8062 2875 718 4799 5729 3095 25842 28564 1770 2414 734 1614 19814 4309 432 8446 473 4419 12692 977 2304 2570 382 682 398 1931 30182 4526 12921 8400 603 4772 2768 359 3640 2737 1915 20501 22858 21607 7231 1832 1220 4741 4435 10613 2047 4250 6556 6053 3216 852 365 939 531 5195 37322 1613 644 1040 6371 777 782 2323 1200 1367 7194 1647 1682 492 27743 1382 7114 12382 766 53744 977 1004 758 962 1971 1903 487 17744 746 9178 2738 1075 10355 813 1196 1732 1292 10207 1078 2494 8536 2064 922 4010 1557 2328 975 15194 6811 1201 7612 10737 931 875 1898 4845 1889 2848 2985 29773 4216 3194 4050 2223 2127 5025 844 5386 11983 4991 1708 10600 421 1534 859 1011 2804 4627 11839 1621 398 60127 2266 3673 13322 798 1103 7724 1102 1858 2441 19384 1483 1167 376 6280 1760 12220 5379 9387 1252 1194 1977 1658 1358 14192 6304 7449 2238 9947 13918 4061 23713 729 6353 7959 1290 10949 698 2033 659 1566 6608 1567 56934 920 3345 2983 1063 1299 2184 2205 5899 2238 777 4806 12796 36362 783 1053 668 10444 660 3721 1907 8711 6289 918 1362 Bacteria;Actinobacteria;Actinobacteria;Bifidobacteriales;Bifidobacteriaceae;Gardnerella;vaginalis;409-05
5 | 3 41 48 54 402 266 426 1193 261 45 228 7704 56 22 499 539 14 147 100 9482 4163 533 226 704 137 16620 10 524 7648 220 27 39 129 193 10529 3864 416 39 106 46 3672 232 1062 31 577 233 109 33 788 61 107 5595 142 40 14 11021 229 21 62 68582 28 49 14399 225 129 206 20 76 55 151 313 313 108 2623 10 100 880 7345 150 270 528 1801 86 6947 107 1021 561 3545 1161 581 757 36 5471 89 22 197 521 26 79 14836 384 632 7586 210 1163 69 640 52 408 2969 20 370 90 1046 235 52 37 228 936 7701 54 15 37 153 495 369 48 33 751 787 330 2420 313 237 1532 572 337 28 100 54 76 155 26 208 41 40 18 63 50 5751 72 401 33 100 131 44 372 1346 387 36 1072 1018 937 348 1327 543 14 59 311 50 1415 118 48 98 697 68 593 151 21 15 617 347 642 20 22777 1156 35 105 3297 261 547 203 291 9 1580 62 65 279 858 139 86 41 236 1170 10 9 238 694 367 46 67 94 5809 336 302 83 1022 18 177 22 89 2178 28770 67 17 133 70 350 111 45 186 1140 5909 71 472 208 42 1204 511 192 26 1132 26 88 20 486 649 669 469 672 819 4452 289 66 29 303 42 322 119 15 13 9 14 43 363 72 587 1257 40 19 6486 301 426 493 27 659 299 88 473 2641 64 294 80 82 568 271 275 265 202 20 66 78 27 139 130 140 239 77 Bacteria;Firmicutes;Bacilli;Lactobacillales;Lactobacillaceae;Lactobacillus;jensenii
6 | 4 193 130 109 83 312 10805 3415 170 549 107 149 228 172 260 341 3300 60 365 146 341 405 79 235 1797 234 4351 9431 215 86 635 1700 127 156 195 189 349 154 152 636 225 425 116 1944 146 116 62 513 186 96 39 371 48 96 115 223 172 489 48 263 2479 2495 120 124 85 202 1707 60 2571 7266 57 108 5533 130 95 145 361 179 62 335 663 175 416 434 246 284 273 282 219 103 549 780 365 1056 2653 102 371 4418 646 159 265 195 155 66 155 380 168 97 11527 85 133 197 50 193 127 44 117 34 523 212 232 3340 7244 59 114 404 40 111 113 107 59 138 11206 936 324 127 271 72 5291 596 159 142 1003 50 195 60 158 54 623 184 457 86 205 2238 97 19 111 140 151 3579 176 264 103 189 270 1015 483 136 280 81 182 240 219 268 318 96 274 36 560 430 98 5309 190 259 177 96 3163 5724 309 712 311 146 1434 1344 330 1481 1271 8707 182 202 111 251 230 626 6666 1152 30 173 22739 7102 676 97 282 534 155 199 173 3014 276 436 76 48 242 125 354 262 309 357 3036 78 78 382 440 154 160 157 4320 212 147 124 4304 196 194 33 87 73 168 279 145 149 193 263 323 133 202 255 1899 85 1777 586 243 884 508 2654 305 30 9678 147 187 45 393 333 227 278 333 335 187 239 292 301 93 4672 78 141 6496 182 7554 123 122 139 365 143 205 153 11648 826 180 467 Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Megasphaera;genomosp.type_1str.28L
7 | 5 179 338 3093 221 264 304 1149 572 543 48 131 79 192 275 441 361 42 463 85 371 1614 917 183 493 228 151 298 162 57 1855 544 282 129 580 155 312 133 1026 262 1037 19421 35 172 258 184 102 353 320 37 41 8112 2285 128 4727 76 187 845 942 97 439 87 701 59 35 460 39 73 134 146 82 90 264 309 394 57 135 230 38 329 5906 243 11897 783 57 658 282 319 222 189 134 247 226 800 261 36 150 160 22 151 1617 6336 25 87 972 603 300 23 12812 114 70 1973 66 201 274 72 145 242 119 9473 5219 1035 3922 57 291 217 40 66 106 353 87 8128 454 60 95 55 7559 85 1253 135 83 1639 3419 217 124 59 177 19 126 7098 359 181 24 2478 72 103 246 221 120 55 140 126 25 787 106 83 477 83 265 75 121 56 73 101 160 38 340 183 4998 226 628 295 186 7026 102 57 1057 261 174 549 258 48 243 160 371 362 100 428 80 535 348 65 75 5769 976 137 1210 415 12207 4167 144 224 453 276 2759 312 421 143 531 243 485 20 156 205 158 230 63 481 675 577 2253 398 225 550 89 106 2259 190 95 253 229 153 136 79 238 15 149 537 6057 11988 319 4847 347 184 336 4531 86 474 301 641 135 334 138 3108 309 52 225 108 122 66 433 598 5242 603 996 296 399 83 265 197 155 428 135 65 113 155 6946 32 122 126 133 55 199 133 23 492 160 407 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;bivia
8 | 6 35 379 6 131 110 606 302 53 11760 182 292 105 19 58 564 360 12 7237 327 406 309 145 17837 68 953 19 194 9914 54 49 5 17 269 32 341 50 6 105 249 143 398 293 143 312 19 386 158 330 75 186 97 17 128 1 652 27 108 78 5916 18 2 905 436 25 420 13 125 69 135 15092 67 248 59 4 40 247 787 100 404 50 16 596 152 65 193 106 133 252 123 331 21 24979 23 212 21 422 78 15 284 29 562 1596 92 434 13 705 15 147 183 24 195 13 363 669 166 5 46 570 328 215 324 229 157 861 278 90 14 215 255 8186 616 217 90 43 402 293 327 156 151 23 32 3 560 193 142 43 25 397 4237 159 227 1 341 89 97 508 45 266 89 583 112 134 498 887 107 14 5 884 109 91 201 108 176 407 28 333 124 219 7 338 139 707 7 286 244 84 598 19 694 157 80 463 108 45 50 336 198 226 30 109 6 247 225 39 37 146 55842 2977 490 15 108 345 57 576 152 26630 104 801 81 53 211 113 16 289 64 68 1626 106 2 582 388 947 8 22 316 8 447 95 455 283 347 254 115 2 83 98 168 226 586 96 127 172 32 90 265 199 470 108 11278 25 2529 2 124 97 33 178 308 73 19 33 328 296 602 14202 157 136 23 194 285 16 12 167 119 332 13326 155 122 117 11 429 12 20 13 55 86 87 5844 Bacteria;Firmicutes;Bacilli;Lactobacillales;Lactobacillaceae;Lactobacillus;gasseri(johnsonii)
9 | 7 158 681 167 247 426 1243 1873 188 310 174 277 347 148 238 119 945 104 311 132 257 623 1825 227 2473 168 1248 2080 1100 154 381 469 319 112 202 155 213 423 1283 434 207 494 125 886 204 146 48 4904 429 99 54 1006 1573 90 81 293 275 339 155 374 224 559 598 46 83 514 693 84 350 3130 91 229 1542 438 104 305 209 291 38 271 782 108 582 266 171 279 158 276 242 218 175 533 307 589 1701 108 251 1281 442 7865 360 810 287 117 126 961 520 88 2475 98 141 4737 113 207 257 46 216 42 269 7183 255 1839 1371 72 398 221 36 137 278 227 123 13462 4164 1498 395 172 803 78 1321 351 90 686 2052 180 74 68 124 42 575 461 434 247 113 610 107 75 541 388 256 779 239 321 42 527 156 1124 1809 138 4513 61 358 138 132 228 232 164 272 89 1251 436 147 1587 201 204 166 86 1156 247 311 476 128 187 704 804 418 425 890 1407 163 256 487 175 121 280 2220 246 98 407 191 1238 364 149 257 358 690 113 495 1637 556 376 435 95 344 233 222 1941 76 699 875 167 3254 221 207 1665 512 134 657 273 254 215 1265 299 149 73 259 39 337 179 1905 3537 453 4244 230 144 1379 955 830 441 2131 409 180 309 492 534 412 114 3372 136 282 92 241 414 1608 511 187 241 334 94 267 221 225 1272 74 88 714 208 4153 116 109 92 526 107 845 731 2213 491 98 401 Bacteria;Actinobacteria;Actinobacteria;Coriobacteriales;Coriobacteriaceae;Atopobium;vaginae
10 | 8 221 144 211 120 357 236 383 219 369 90 64 265 127 188 474 6309 26 352 400 98 1897 505 86 2720 190 4922 7546 123 41 2875 2869 104 137 287 88 319 35 89 747 223 1385 155 1261 121 200 99 491 93 14 38 505 327 161 123 163 181 785 354 301 1408 3055 61 230 187 155 141 84 272 339 119 97 249 124 136 57 99 175 16 258 497 107 6259 145 445 383 141 295 211 104 408 2129 272 256 1229 181 50 4480 1482 341 229 105 123 13 80 102 119 122 1349 34 146 175 40 149 76 47 141 37 368 242 370 3707 3824 71 70 294 48 95 152 59 72 347 2343 1679 873 120 571 22 7800 265 72 174 901 102 203 32 142 161 265 777 276 98 542 4181 54 34 92 174 156 283 192 214 20 210 233 2913 504 300 66 93 80 77 102 224 176 287 227 91 417 1265 64 5705 175 251 92 82 828 4158 189 123 196 132 3241 547 4714 1769 3074 791 153 188 977 127 67 525 3955 2697 62 202 16743 8246 4866 60 88 422 518 297 239 1056 291 570 143 21 135 149 219 538 116 286 3882 341 71 432 139 752 107 136 166 228 63 102 2101 91 252 77 2162 21 117 222 4661 51 99 179 246 144 306 187 338 147 11136 896 2506 1285 482 1854 182 69 6013 84 157 139 367 4466 1592 281 291 221 167 71 141 165 200 3837 69 23 172 55 13684 37 42 151 284 55 1358 801 59 3183 130 338 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;timonensis
11 | 9 109 191 66 13 443 29 71 10 432 7 4 19 42 4 76 224 27 202 264 142 84 183 11 12 94 17 2870 70 48 27 221 12649 121 17 49 125 161 308 55 10 661 75 1130 16 15 101 937 16 14 122 23 39 104 108 161 104 22 15 99 3518 8047 295 58 593 579 6 132 96 44 127 299 380 428 66 129 119 21 30 16 115 95 109 13 226 126 11 90 18 96 110 1536 29 55 8956 153 43 1853 256 14 631 21 53 17 12 286 225 139 166 108 46 7950 34 84 298 102 66 123 117 506 115 191 362 75 256 22 47 10 97 12 13 145 122 230 537 43 21 60 47 97 97 21 188 165 148 62 81 116 240 280 45 2 202 153 78 130 198 253 68 20 23 111 40 549 121 320 91 326 369 204 263 41 34 43 288 217 30 92 199 105 6 128 75 215 13 53 198 213 271 21972 16 259 1131 3304 635 3491 123 365 45 78 111 34 2 25 13 126 66 359 10 234 381 80 47 491 405 108 342 44 270 226 35 12 378 18 109 162 30 278 8037 18 315 24 49 2418 273 152 87 382 77 156 360 83 111 1997 20 14 467 13 19 14 381 494 105 59 42 48 81 224 61 42 49 58 110 140 708 57 5179 44 72 13 201 46 126 425 173 233 295 93 167 129 78 5250 189 150 1783 7 13 24 88 50 170 116 595 41 2681 80 3 207 Bacteria;Actinobacteria;Actinobacteria;Bifidobacteriales;Bifidobacteriaceae;Gardnerella;vaginalis;WGS101
12 | 10 185 27 42 87 66 57 1911 445 191 64 4 158 38 299 286 3854 41 171 48 80 139 51 9 307 28 7108 2726 65 52 450 28 26 39 219 6 234 133 151 233 9464 31 43 305 171 149 29 1015 117 41 42 319 21 49 9 106 72 438 1514 156 120 464 19 34 28 82 761 34 249 111 49 49 367 141 68 39 58 51 21 27 259 107 2573 294 51 765 236 346 124 236 329 69 153 329 103 22 32 480 271 94 29 59 50 45 3 396 21 39 11061 24 71 69 110 142 20 12 16 10 76 97 553 687 98 19 20 298 21 105 110 89 86 66 24 1100 57 102 128 8 1027 192 20 74 30 32 144 26 12 32 144 81 179 73 59 99 42 67 24 69 120 121 131 74 18 51 100 115 96 45 28 16 45 47 58 177 177 57 29 20 1357 131 21 1905 128 34 102 60 186 1084 56 98 293 39 2366 56 71 100 56 2785 77 30 17 102 10 315 1171 123 23 53 13279 127 284 66 90 210 173 34 68 191 52 176 20 19 45 128 99 881 202 69 238 1272 171 315 213 34 40 71 20 59 44 20 195 78 78 33 4153 19 48 201 39 51 54 114 95 20 6414 120 77 55 3007 256 52 546 424 3840 128 37 1428 56 46 107 273 3402 402 44 49 57 30 40 48 15 133 702 70 94 53 24 2689 20 7 14 81 47 738 535 48 352 142 73 Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Leptotrichiaceae;Leptotrichia(Sneathia);amnionii
13 | 11 32 45 34 62 139 173 621 185 126 45 17 94 19 322 223 2393 23 130 41 25 367 40 12 96 11 408 1049 15 37 70 62 58 58 202 7 291 57 78 197 288 106 16 660 64 45 12 395 90 20 15 820 56 52 17 39 93 73 1 77 672 23 37 9 18 83 213 25 126 393 24 54 1058 65 38 37 21 31 7 65 8204 105 68 273 38 118 203 260 96 25 184 142 141 17 132 28 13 336 372 58 83 31 60 2 9 1512 27 18 321 18 27 72 11 57 20 10 58 7 129 119 110 984 142 14 29 165 7 19 62 8 28 33 111 573 52 34 115 8 4378 78 36 26 1302 25 75 10 8 16 346 75 137 76 16 212 23 13 65 70 76 44 84 100 9 92 23 79 78 43 36 21 71 56 42 95 60 17 41 12 158 74 6 110 47 24 58 14 113 352 107 65 323 53 1167 87 138 14 1624 3103 35 30 164 32 5 9362 85 49 8 43 12201 176 35 29 52 180 50 24 54 139 107 109 26 18 41 27 87 62 66 129 22 199 18 284 220 32 81 32 27 63 34 35 3012 36 59 22 413 2 81 171 17 14 130 154 99 32 358 145 76 58 584 140 15 210 58 82 89 25 308 35 75 12 276 107 1239 81 50 76 50 46 33 40 35 518 17 22 47 17 7558 9 6 22 97 35 966 758 7 39 179 133 Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Leptotrichiaceae;Leptotrichia(Sneathia);sanguinegens
14 | 12 17 5 48 23 224 51 165 36 6798 13 208 65 9 134 10 215 8 3905 8 108 580 11 24 26 33 17 32 16 10 6 19 5 11 6 44 30 7 73 25 54 229 123 18 55 7 2 42 225 11 42 49 119 110 4 16 28 35 45 1134 31 6 423 2 25 65 1 6 44 7 43 48 57 44 4 16 56 122 47 259 7 9 3 165 17 47 8 3 46 46 1863 5 2350 8 103 334 33 18 8 31 2479 54 228 132 120 11 84 4 61 109 110 12 23 156 108 289 63 2 53 138 104 454 134 8 208 60 0 3 83 48 49 88 29 41 29 93 213 1 20 6 17 5 21 162 26 2 18 18 156 178 84 134 3 130 12 29 358 11 35 3 113 22 13 121 31 21 38 7 104 20 20 18 217 37 156 1 1955 85 162 2 63 28 20 6 88 74 4 117 9 242 66 11 273 66 31 13 317 82 28 56 25 0 18 14 97 4 22 102 45 164 4 4 41 77 64 16 13194 2 530 1 6 150 25 43 91 9 47 159 6 5 125 93 5 19 156 25 9 16 14 56 186 428 189 5 15 5 86 9 13 227 155 35 33 31 14 14 79 81 9 104 28 28 6 4 62 43 26 1806 176 20 5 45 72 145 150 64 33 4 13 62 1758 16 63 53 53 546 219 13 15 4 266 2 0 5 3 53 3 20194 Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;unclassified
15 | 13 219 378 354 43 274 553 583 121 274 64 44 133 122 23 43 652 26 182 1031 163 300 122 2450 859 57 3595 5017 248 171 351 424 452 76 35 78 178 551 2795 763 125 3062 103 483 131 124 26 6693 85 68 29 274 131 100 56 181 487 133 234 120 201 169 188 26 429 491 1749 68 929 232 40 109 289 821 96 376 219 104 36 181 202 70 132 28 96 525 118 152 263 151 246 242 699 612 628 67 198 3788 147 129 331 82 52 38 65 1230 389 67 259 18 113 268 76 97 272 28 41 32 194 187 77 687 961 54 199 200 20 121 189 108 79 3149 1340 142 282 58 154 247 677 325 120 709 749 174 112 40 83 27 2384 2463 158 48 110 187 63 65 153 121 170 197 106 339 42 548 62 268 1373 117 4268 81 183 114 118 131 212 98 271 18 360 313 65 4711 62 200 81 58 884 110 402 946 44 119 860 454 413 273 522 1318 135 204 629 199 48 156 2299 235 103 158 255 2162 2128 360 189 342 600 48 281 179 551 344 218 20 241 113 135 10622 570 1060 563 61 2360 70 237 1339 115 124 529 90 266 167 270 47 102 21 554 40 172 125 271 84 107 187 177 74 357 214 511 138 1661 1898 118 3039 189 401 305 147 2053 86 372 74 192 190 182 6047 155 306 175 104 179 205 335 2859 640 113 577 1740 2101 93 73 57 145 105 567 204 2077 282 45 116 Bacteria;Actinobacteria;Actinobacteria;Bifidobacteriales;Bifidobacteriaceae;Gardnerella;vaginalis;HMP9231(1MM)
16 | 14 80 17 22 8 59 3091 19 2 142 28 52 91 24 2 3 6492 2 66 88 68 39 16 33 41 30 1277 1060 48 12 543 153 681 15 6 52 16 17 57 207 3 55 9 3334 8 31 1 4509 4 6 2 41 13 2 27 54 45 100 9 25 60 1355 13 0 32 78 2627 18 104 1417 11 67 174 40 59 14 13 32 2 31 41 26 86 5 56 99 10 31 43 4 114 351 25 12 154 23 42 708 718 11 60 32 10 2 31 61 15 22 40 1 60 92 2 7 48 8 17 7 42 81 50 313 184 3 14 34 22 19 28 26 7 11 3576 40 57 4 5 6 76 99 5 26 34 23 18 3 44 28 640 9 136 7 292 64 8 0 13 49 25 3442 3 57 5 22 10 625 64 54 27 5 36 15 3 61 52 54 87 0 52 342 38 36 5 48 4 12 232 278 48 59 2 121 615 79 179 44 60 327 19 49 34 39 112 48 50 627 4 11 74 174 94 12 10 143 320 20 12 886 16 214 48 0 49 39 79 39 26 66 25 25 5 17 20 35 54 8 23 38 15 85 58 7 69 2 24 27 84 12 37 44 127 102 25 31 68 31 966 9 1216 111 840 277 1264 160 128 21 42 17 11 46 67 98 29 61 74 20 65 13 111 44 22 442 17 13 517 15 6 4 34 57 109 25 55 781 8 30 49 121 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;amnii
17 | 15 103 91 71 22 2 15 35 21 99 22 6 77 29 93 64 52 30 27 182 51 67 76 2 88 40 68 11 170 5 75 3066 35 41 58 25 32 61 71 93 21 103 72 97 5 67 39 176 7 3 44 89 2 34 56 82 27 102 20 127 141 161 7 28 105 45 1836 29 3 42 50 18 41 1 111 22 111 15 9 3 123 63 113 63 106 122 14 54 21 55 79 926 16 29 72 30 30 86 1516 5 16 2 92 6 6 32 5 45 3922 43 57 10 1 62 39 34 76 50 114 15 59 43 123 22 17 4 35 29 17 2 25 1 65 95 20 24 8 25 68 116 30 32 65 41 36 8 49 94 65 4 99 2 2890 27 21 24 4 24 15 87 17 38 13 37 157 151 63 83 21 46 1 8 3 82 167 80 29 47 40 139 23 23 25 82 12 93 228 4225 123 68 59 13 2422 65 16 63 29 133 40 93 16 70 18 53 47 4515 47 38 46 56 1934 11 15 3 37 78 18 39 4 127 22 2 1 114 19 37 5 19 87 77 5 50 43 76 5 47 71 24 3 30 43 85 38 38 34 23 6 16 30 7 4 2 56 87 53 47 39 41 144 88 1490 83 2274 99 45 60 8289 26 1 77 93 110 47 43 63 107 23 55 34 21 0 60 89 36 2786 0 36 1 36 95 48 49 52 48 16 61 55 35 Bacteria;Firmicutes;Clostridia;Clostridiales;unclassified;unclassified;BVAB1
18 | 16 47 62 40 20 110 534 321 108 115 30 31 67 30 104 127 712 1 134 33 69 525 279 31 592 50 884 974 81 52 168 404 47 45 100 48 166 448 603 78 3848 104 53 478 60 44 21 689 46 7 30 128 559 61 62 56 85 129 23 77 285 493 26 9 27 102 349 30 124 634 32 44 539 57 27 82 53 47 11 90 178 68 99 177 67 70 81 120 38 63 75 71 44 179 1011 34 58 582 215 20 89 84 49 8 26 1134 36 29 1848 47 55 62 14 73 53 26 43 22 95 66 50 1063 814 20 27 42 10 35 95 36 9 27 1394 264 59 23 169 17 421 84 33 40 703 20 43 21 33 23 122 83 110 17 140 253 21 15 37 45 27 423 36 94 17 94 44 798 59 68 29 38 32 15 38 50 82 31 58 23 755 135 24 1158 36 68 15 30 587 125 132 90 136 56 489 356 73 131 183 314 39 43 384 44 35 141 837 414 99 29 617 655 237 24 29 67 118 38 45 114 99 156 172 13 39 70 66 482 18 58 234 58 34 149 140 599 53 74 31 57 74 36 861 64 47 15 454 10 51 116 118 78 69 96 61 40 74 965 698 23 947 140 99 113 140 302 85 54 2007 40 142 24 196 92 139 61 98 111 72 31 92 73 54 1392 40 26 134 31 4284 9 35 38 102 32 363 239 249 508 63 140 Bacteria;Actinobacteria;Actinobacteria;Coriobacteriales;Coriobacteriaceae;Atopobium;rimae
19 | 17 14 37 1 23 29 93 85 32 461 23 2518 16 4 49 66 14 57 19 8 41 77 59 31 6 40 2 81 59 270 17 2 16 107 17 93 48 18 18 33 48 40 6734 44 30 4 804 12 89 228 47 31 39 20 7 703 22 7 40 3686 6 2 62 89 672 98 1 14 10 6 26 85 41 393 4 48 4509 67 834 31 23 507 8 28 20 113 179 568 281 315 127 8 1154 5 13 7 79 9 6 92 1107 39 119 79 109 23 80 8 32 33 30 510 71 501 124 71 12 32 2254 44 7 7 3 205 144 1080 71 37 67 681 21 342 25 12 65 97 90 44 10 32 856 11 6 395 17 159 29 3 39 56 3 41 7 12 44 47 1798 340 24 2 53 50 7798 57 107 69 1 12 82 32 21 289 46 42 108 6 39 22 14 4 30 23 25 4 76 113 4 8 11 48 85 491 17 8 30 27 16 29 75 3 39 11 26 94 2 7 10 62 25 33 3 58 772 28 252 75 89 6 30 6 16 79 17 3 7 17 65 252 1 0 47 55 51 31 188 27 9 40 158 598 17 301 12 9 0 28 111 26 82 49 36 104 17 19 9 84 9 32 5 3 6 1 5 6 48 8 84 72 7 1 597 23 25 53 446 127 85 48 738 64 11 28 293 208 177 38 19 288 110 3 45 47 3 12 110 9 40 14 Bacteria;Firmicutes;Bacilli;Lactobacillales;Lactobacillaceae;Lactobacillus;vaginalis
20 | 18 70 15 71 69 46 2182 281 279 80 68 61 62 63 268 67 70 44 29 67 192 412 41 120 50 58 63 185 4466 18 42 86 24 24 89 33 65 22 91 266 91 89 358 123 76 49 16 525 102 41 81 5372 9 13 45 52 49 58 190 362 319 60 150 41 1123 61 28 8 244 534 10 23 528 126 86 29 149 65 178 68 70 52 1260 139 58 150 40 37 109 265 150 55 61 213 119 81 99 117 59 108 31 55 103 98 188 41 202 34 397 26 85 25 160 101 66 17 114 9 118 39 26 254 20 48 367 95 23 290 27 181 48 63 524 463 79 59 74 1730 95 77 37 1481 80 65 32 7 66 26 90 132 100 72 24 73 40 82 70 33 35 196 67 35 32 80 93 87 4514 25 1233 24 16 61 83 147 271 21 96 10 229 104 56 111 48 58 241 66 155 28 26 292 214 43 46 45 94 343 85 210 64 2799 133 50 55 80 89 66 230 123 156 34 80 583 71 41 55 80 114 652 151 55 36 36 110 106 16 28 76 123 574 21 5711 83 153 1875 28 37 109 37 85 98 12 177 17 21 207 39 214 138 52 80 67 42 51 165 773 684 75 109 166 96 73 119 22 70 341 14 380 43 58 38 53 1566 3756 167 17 83 95 50 27 42 437 153 58 135 87 27 867 120 39 43 113 13 23 17 504 191 60 41 Bacteria;Firmicutes;Lactobacillales;Carnobacteriaceae(Aerococcaceae);Granulicatella(Aerococcaceae)
21 | 19 25 66 265 25 42 485 257 74 85 23 85 32 19 92 75 214 23 316 31 107 230 69 61 170 86 150 299 2913 10 269 83 21 17 324 77 75 17 37 80 1989 414 83 161 49 33 10 364 47 16 10 863 132 15 52 54 30 43 41 80 97 58 112 28 100 64 41 12 46 206 11 19 126 92 18 14 74 69 7 89 563 33 1057 142 32 530 60 60 33 68 85 85 184 60 84 17 70 372 158 17 422 1081 62 36 92 18 46 12 1590 28 25 679 24 119 57 13 21 8 77 757 157 273 314 12 88 31 18 40 34 69 9 636 805 214 62 26 212 234 511 55 14 162 63 28 10 11 33 7 90 2264 83 17 22 124 8 12 48 30 27 182 25 17 14 185 92 82 117 19 88 11 27 26 18 39 82 23 82 8 148 95 54 607 36 43 24 45 169 672 36 77 83 90 156 43 247 133 97 452 38 160 48 26 83 1143 267 48 66 100 554 420 88 87 44 38 207 33 237 162 78 41 62 10 19 29 24 58 25 116 211 117 1273 99 65 347 24 32 38 48 10 62 169 96 19 15 208 25 66 55 1873 3968 58 202 37 23 512 1008 85 70 308 75 44 80 108 257 39 11 1012 27 16 11 69 202 334 87 213 85 40 30 64 72 101 134 22 26 110 54 1429 10 39 73 38 10 37 51 80 141 72 161 Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Dialister;micraerophilus
22 | 20 44 43 28 10 33 337 208 22 138 15 28 54 20 15 20 337 14 125 89 46 107 37 12 894 34 378 1301 59 16 153 95 24 45 16 22 44 35 63 77 15 59 32 592 25 66 16 116 24 5 20 24 46 24 18 83 81 37 7 141 414 989 20 8 55 68 170 22 71 101 33 21 119 21 37 41 45 44 2 54 55 13 59 8 100 100 0 29 34 115 57 153 44 19 915 35 31 1927 470 9 64 26 67 11 18 68 10 20 62 41 38 49 21 70 20 21 43 9 119 58 79 234 1899 11 16 19 13 30 122 33 10 10 917 518 23 39 17 12 1143 57 40 24 935 11 18 12 13 28 123 25 57 12 176 74 13 19 21 27 38 47 33 100 10 70 58 1108 49 57 15 43 12 39 33 51 75 57 35 18 2465 131 17 725 20 41 14 23 133 191 108 97 7 41 998 481 41 647 784 35 12 52 47 51 22 49 1275 86 12 25 13 1802 423 34 21 26 55 51 54 132 27 91 33 8 12 102 53 1423 25 53 1338 45 40 40 9 70 48 59 31 34 15 18 462 62 77 18 33 10 35 5 16 28 22 22 53 26 58 9 378 10 1277 69 87 69 1562 55 33 32 2279 11 65 27 60 88 23 38 90 161 26 40 50 71 57 1083 28 15 95 11 31 5 18 14 175 42 303 656 208 894 7 271 Bacteria;Firmicutes;Clostridia;Clostridiales;unclassified;unclassified;BVAB2
23 | 21 0 0 13 0 1 2 3 2 148 0 1 2 10 0 42 17 2 18 0 2 3 5 1 34 57 1 2 1 3 1 17 4 0 1 14 3 16 4 2 6 201 141 18 1 0 24 0 1 2 3 0 2 1 372 0 3 2 1 72 27 0 151 27 0 182 0 0 1 3 23 2 130 0 2 1 2 43 3 1 0 4 59 1 1 4 1 0 1 3 4 16 3 9 20 0 1 0 0 1 1 2 2 2 3 13 122 0 3 2 10 1 2 3 183 7 19 3 2 76 11 15 19 0 176 3 0 0 54 1 1 150 2 32 0 51 6 1 1 0 1 0 7 108 0 1 17 1 16 167 2 0 3 13 4 0 113 0 0 1 54 1 10 218 50 12 26 5 181 2 0 2 3 1 6 0 3 0 13 0 0 6 33 735 3 5 1 71 1 160 3 0 78 15 2 7 7 0 1 9 14 1 0 2 0 4 0 9605 0 16 0 0 0 0 129 64 13006 0 191 8 0 0 3 1 6 0 3 244 36 1 234 75 3 0 2 52 12 71 1 72 18 2 9 0 0 0 4 0 5 1 1 3 0 22 3 7 8 131 2 0 12 4 9 2 7 0 1 11 1 0 6 69 3 179 1451 3 14 2 9 0 0 3 2 3 35 0 0 2 7 15 18 6 0 0 1 77 1 23 Bacteria;Actinobacteria;Actinobacteria;Bifidobacteriales;Bifidobacteriaceae;Bifidobacterium;unclassified
24 | 22 39 30 21 8 12 8 46 1 42 7 0 15 9 0 1 180 5 36 5 10 676 2 2 15 1 898 181 73 5 20 415 8 7 2 2 16 6 16 20 1 81 52 186 9 19 0 22 17 0 1 8 5 2 14 73 9 12 0 69 432 49 5 2 1 28 13 8 20 12 0 2 74 1 11 10 54 2 1 5 69 10 11 2 7 109 1 23 24 44 103 142 25 9 1381 0 0 36 0 14 15 2 65 1 0 19 0 0 14 0 12 20 0 49 4 1 12 3 84 2 18 37 147 0 2 19 0 11 13 2 8 3 51 0 3 0 17 4 9 12 4 17 24 1 7 1 8 2 49 6 15 7 7 13 14 1 3 1 16 14 11 19 1 9 66 103 37 11 4 5 2 8 3 10 75 12 8 0 60 85 0 1274 10 32 4 41 120 25 59 13 2 4 38 609 8 3 25 67 30 20 9 8 1 11 23 381 0 5 19 55 26 19 11 18 25 15 4 10 4 47 5 2 2 13 17 562 9 15 0 11 2 0 6 12 1 9 9 4 4 6 48 50 20 1 20 0 3 2 2 3 3 3 54 14 15 4 22 3 811 33 4 35 36 53 10 8 7485 8 12 10 28 13 9 9 28 81 1 21 21 7 3 182 4 3 51 1 8 1 8 16 42 12 1116 9 0 18 5 77 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;marshii
25 | 25 30 24 30 12 20 365 158 17 52 14 41 25 13 19 29 267 11 29 19 31 84 80 7 226 25 291 204 28 12 1989 86 18 44 26 29 30 83 35 82 793 263 34 409 25 31 26 157 19 2 20 201 40 14 14 39 45 24 27 44 202 296 24 22 11 44 61 14 28 70 35 17 68 15 25 11 37 46 6 25 168 13 500 42 35 55 9 24 24 18 39 62 40 37 131 12 25 256 96 18 22 41 27 6 27 65 16 9 338 21 26 179 4 41 36 10 16 9 86 24 28 251 278 16 15 26 13 14 39 14 11 14 387 77 106 27 283 5 106 34 11 22 173 12 23 8 22 9 29 656 33 13 31 14 8 13 22 18 17 17 26 71 16 51 42 510 22 16 22 22 9 50 12 25 60 16 39 26 109 223 10 419 27 47 15 16 69 454 61 27 28 22 245 108 129 90 54 20 34 17 32 27 17 82 92 110 7 39 35 795 48 14 27 35 72 13 41 85 37 40 14 4 15 19 12 37 10 93 166 25 61 52 16 25 17 24 23 33 11 23 39 36 10 13 83 1 15 19 1086 12 19 27 38 13 21 520 56 24 1169 54 53 65 97 87 34 10 2255 16 26 17 56 62 232 41 66 50 42 31 33 28 15 149 24 20 128 8 346 7 13 9 28 10 44 44 36 260 23 37 Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Dialister;propionicifaciens
26 | 26 8 2 14 16 7 31 30 27 17 6 42 7 1 39 26 15 15 12 10 69 95 18 23 40 28 7 52 14 0 17 24 3 1 37 43 26 5 13 3 31 542 5 32 10 5 2 159 26 1 1 36 162 2 1 4 4 13 10 10 8 23 38 2 3 9 10 0 2 3 2 0 11 4 19 2 5 57 1 43 34 12 7 67 6 11 18 28 5 18 11 11 5 9 11 2 34 9 1 1 3 1666 8 10 40 13 3 0 171 4 11 3 3 24 16 2 2 1 7 5 1043 71 19 1 15 4 0 6 13 54 2 7 72 31 4 2 270 33 59 1 3 6 5 10 4 1 7 2 9 116 4 11 9 8 2 3 15 10 8 29 7 10 12 19 4 87 5 25 7 1 2 1 11 4 16 1 52 1 127 28 44 39 5 0 8 4 45 28 41 17 32 5 60 6 4 15 14 21 13 14 50 12 28 45 34 8 0 7 84 12 7 2 3 4 96 2 9 0 24 7 67 0 3 14 1 6 3 9 11 930 9 30 19 200 4 3 0 1 6 24 8 31 6 5 138 1 3 12 293 3269 15 13 12 2 4 1173 7 23 50 10 6 8 13 7 10 7 222 4 9 4 15 4 255 11 17 14 19 9 31 39 9 49 4 5 9 23 693 0 17 1 12 4 6 29 2 16 9 34 Bacteria;Firmicutes;Bacilli;Bacillales;Bacillales_IncertaeSedisXI;Gemella;asaccharolytica
27 | 27 26 1 17 5 3 16 11 9 27 3 12 4 9 6 21 24 6 8 38 15 25 1 7 48 16 256 8 13 1 122 18 4 4 13 9 27 3 13 8 0 9 18 5 3 18 11 19 1 1 3 9 5 0 9 21 3 14 212 16 28 44 2 42 30 7 17 5 6 10 3 2 1 12 12 13 11 21 5 15 234 3 22 3 40 7 1 14 0 36 12 796 2 13 20 30 13 40 888 11 20 2 9 3 14 11 22 12 12 2 7 13 3 3 1 1 11 6 15 10 21 38 52 5 9 2 1 8 7 13 1 1 11 37 45 11 61 1 4 6 20 20 27 7 2 1 6 29 24 3 4 0 32 23 3 4 2 7 7 5 11 8 2 33 18 52 23 25 6 7 0 7 3 9 16 44 8 2 939 41 8 8 12 23 9 11 16 1284 12 14 9 3 30 13 15 19 3 0 28 17 1 17 5 9 16 5 3 19 14 88 21 13 5 3 20 35 12 1 8 8 5 4 8 20 7 157 7 14 38 30 24 12 7 43 0 25 19 12 12 2 48 4 18 1 211 4 16 15 1103 4 0 0 4 42 20 3 13 12 20 13 178 6 513 299 15 10 758 1 7 21 9 9 10 1 4 29 9 8 7 28 23 3 5 9 3 4 443 7 4 12 29 8 70 10 7 112 8 2 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;unclassified
28 | 28 25 3 2 1 2 0 73 1 46 1 10 0 1 4 5 0 2 0 0 50 63 2 60 0 0 1 1 65 0 0 1 147 57 12 3 6 1 126 1 4 5 78 0 3 0 3 57 0 0 0 4 1 4 0 71 0 0 1 84 25 3 0 0 0 1 2 1 1 2 1 0 2 1 10 0 70 1 0 0 2 0 0 10 0 96 1 4 1 51 110 0 0 4 0 1 3 0 0 3 5 1 151 0 1 2 9 0 90 6 2 4 0 65 3 221 0 4 74 3 0 0 3 58 3 1 3 1 1 1 1 0 2 0 8 0 0 2 0 0 1 1 2 1 3 0 1 0 0 1 2 1 0 6 2 2 0 3 0 2 0 3 1 0 71 38 2 0 1 2 0 2 0 0 11308 0 0 1 0 1 9 0 1 0 1 47 1 2 12 87 3 10 2 1 5 0 0 0 52 0 2 1 1 6 0 0 0 1 9 2 0 1 1 6 2 0 0 1 1 1 10 0 6 0 0 1 0 3 0 1 0 2 5 2 5 2 0 2 11 4 0 134 1 2 0 0 6 807 1 0 3 1 1 0 0 6 1 14 0 1 0 0 0 0 61 1 61 1 2 1 5 1 56 0 0 58 0 2 0 0 1 3 33 33 50 0 8 2 3 2 0 2 0 2 0 0 17 1 Bacteria;Proteobacteria;Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;unclassified;unclassified
29 | 29 35 20 10 6 8 14 35 50 41 1 0 3 1 12 17 19 6 3 4 16 29 11 2 109 6 30 4 5 1 275 13 14 11 22 4 8 1 8 15 22 785 6 6 1 14 7 9 4 0 10 41 8 14 2 3 3 38 18 24 18 13 14 17 4 12 6 11 12 4 16 5 2 16 11 1 0 21 0 11 1115 11 6 22 11 3 7 9 6 25 1 3 12 8 16 3 2 6 1 3 1 8 3 0 4 5 5 2 1205 11 13 5 20 1 5 9 3 7 12 25 9 83 110 3 9 3 9 9 17 26 2 3 23 13 7 19 27 1 9 1 5 11 28 6 8 0 4 3 6 61 3 6 1 10 1 11 11 5 8 1 21 6 0 16 9 10 8 10 6 23 0 2 6 2 9 1 5 84 48 110 2 111 6 18 12 4 19 246 10 25 11 0 66 12 1 1 4 1 20 1 4 13 2 25 665 1 2 10 18 256 19 2 6 2 5 16 46 0 22 12 37 1 0 18 1 4 0 15 5 37 47 39 6 1 2 6 2 6 0 12 7 3 1 10 2367 0 7 7 600 5 9 3 13 2 21 11 5 23 7 16 2 3 26 49 9 2 7 6 12 13 28 65 286 7 6 10 167 4 9 10 18 21 15 3 3 5 427 0 3 3 13 4 33 7 0 179 13 10 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;disiens
30 | 30 3 16 11 5 2 19 0 5 5 4 1 20 8 8 8 5 0 6 12 3 2 8 0 4 2 2 17 13 3 22 51 14 5 74 0 6 226 3 64 104 135 1 26 2 5 0 71 1 0 2 1664 1 0 28 0 20 20 1 65 18 18 10 0 1 11 10 0 3 20 0 1 181 3 14 0 14 2 0 1 61 20 20 9 7 17 1 3 17 5 8 14 14 8 7 0 0 31 1 1 2 5 0 1 3 10 3 0 15 1 0 0 1 3 2 0 17 2 23 1 168 1 46 0 3 5 7 7 1 1 0 2 30 3 16 0 29 4 31 24 1 4 10 2 1 0 6 0 5 5 32 0 4 7 9 1 8 0 1 61 1 10 0 19 0 3 20 2 2 1 0 2 0 19 0 0 23 1 99 50 1 4 1 31 80 0 6150 3 26 4 11 13 1 11 22 1 3 2 0 26 13 2 7 34 1 33 1 2 158 16 19 1 1 4 6 11 6 9 7 32 15 0 1 9 4 3 0 36 0 3 5 9 6 52 2 1 12 0 1 30 5 0 2 0 3 7 2 4 5 1 0 2 11 17 33 22 11 7 81 41 8 37 330 30 2 1 28 1 1 1 7 36 1 36 2 1 0 17 5 3 3 24 1 0 1 1 7 0 10 1494 2 2 3 5 0 12 17 2 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;melaninogenica(histicola)
31 | 31 4 9 15 15 11 6 51 14 5 9 12 5 25 10 18 54 0 4 15 13 299 2 2 107 9 29 25 0 4 136 62 14 2 16 5 24 26 18 3 13 29 54 35 11 7 0 44 14 2 0 121 7 3 901 8 6 20 52 8 64 26 19 5 42 31 3 1 15 3 1 7 39 10 17 7 5 13 6 6 838 17 6 23 9 13 15 12 20 7 15 28 36 44 12 6 5 10 12 16 312 10 4 2 3 31 16 13 41 0 13 5 2 17 6 3 39 6 7 11 4 37 11 1 12 31 1 6 10 8 10 11 19 15 165 4 401 6 43 3 4 6 63 15 4 0 22 5 3 871 5 13 15 40 14 1 8 2 15 3 20 11 6 47 11 23 40 22 11 11 3 4 4 2 5 7 11 10 12 13 11 31 12 1421 13 4 29 7 35 18 20 4 4 9 17 95 6 326 14 48 150 6 6 19 30 12 0 12 381 5 14 2 33 5 43 25 11 4 16 20 6 0 7 10 4 71 4 22 163 8 18 18 12 812 9 10 23 9 4 5 10 4 4 1 14 0 21 10 542 5 7 25 21 38 16 77 2 8 47 11 31 8 190 56 10 4 32 14 7 11 35 8 135 16 4 16 6 7 7 18 5 14 1 1 9 6 206 2 15 25 6 7 5 10 2 33 22 2 Bacteria;Firmicutes;Clostridia;Clostridiales;Clostridiales_IncertaeSedisXI;Anaerococcus;tetradius
32 | 32 0 1 0 0 0 0 27 2 1 1 1 0 0 1 1 1 1 1 40 0 31 35 0 0 0 0 1 28 0 1 2 0 0 0 1 0 0 0 0 0 0 37 0 0 1 0 0 0 0 0 93 2 0 0 21 67 0 1 51 0 0 0 0 0 0 0 3 1 1 0 0 0 1 0 0 31 0 1 1 0 0 0 2 0 10150 0 1 86 21 50 0 0 0 0 0 0 0 1 1 0 0 46 0 0 0 2 0 0 0 0 1 0 54 0 0 0 0 45 0 72 0 1 0 2 0 0 0 0 0 0 0 0 1 2 0 1 0 0 0 1 1 1 0 0 0 0 0 1 2 0 0 0 0 0 1 0 0 0 0 0 1 0 0 36 35 0 0 1 0 0 2 1 0 53 0 79 0 0 0 0 2 0 0 1 30 0 1 0 1 1 0 2 0 57 0 1 0 31 1 0 0 0 1 0 0 0 1 0 0 33 0 1 1 0 0 0 1 0 0 0 0 1 0 0 0 1 1 0 2 0 0 0 0 1 1 0 0 1 0 3 60 0 0 0 0 2 0 1 1 0 0 0 0 1 1 1 3 49 0 0 0 0 0 0 1 47 0 0 0 1 0 0 121 2 40 1 1 0 1 0 1 0 0 23 1 0 0 0 0 0 1 0 0 0 0 0 3 Bacteria;Tenericutes;Mollicutes;Mycoplasmatales;Mycoplasmataceae;Mycoplasma;unclassified
33 | 33 3 6 38 23 15 5 8 15 322 53 9 5 20 18 14 16 31 5 36 15 5 4 9 3 4 3 9 74 6 50 54 4 4 1240 3 17 6 13 17 28 9 75 0 6 2 2 3 8 1 24 18 1 2 91 2 8 23 40 19 45 50 20 7 65 8 18 1 1 1 8 38 6 8 6 23 45 21 46 5 10 6 4 15 27 41 7 4 3 8 14 24 4 30 3 22 26 4 45 2 12 2 4 7 63 9 6 20 14 5 7 5 5 5 6 2 45 1 7 12 20 10 8 4 72 7 28 2 12 12 23 8 6 34 216 21 9 3 2 7 9 0 32 50 4 2 25 42 13 7 6 5 14 5 3 1 7 44 0 38 8 8 3 23 4 2 62 20 39 4 4 2 3 25 7 29 6 15 3 49 279 1 1 154 53 39 2 6 10 7 53 53 12 1 541 12 5 6 8 67 2 9 53 12 3 1 19 4 13 8 5 1 29 11 3 31 19 0 6 2 76 4 9 1 2 0 3 3 29 12 6 24 24 22 13 0 43 5 8 124 3 10 28 29 2 57 48 9 36 9 14 7 8 57 6 6 37 67 5 3 69 3 0 2 5 37 10 3 5 11 5 4 7 18 31 68 9 3 4 5 6 12 1 8 3 5 13 1 6 2924 22 1 3 45 11 53 62 8 Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;unclassified
34 | 34 10 11 0 1 1 5 5 1 37 1 0 1 0 0 0 44 0 59 0 6 14 0 1 3 0 4 318 31 1 7 5 16 6 1 1 1 22 9 2 0 25 12 0 0 6 0 52 3 0 0 1 0 0 9 12 1 0 0 11 5 5 3 0 0 36 77 0 0 0 0 6 14 1 9 1 8 2 1 0 10 13 0 1 2 11 1 1 2 6 10 2 2 0 3113 0 4 0 1 0 1 0 21 1 2 37 0 0 12 1 4 6 0 4 4 0 0 10 24 9 24 28 89 0 1 1 2 2 1 0 0 1 12 0 4 1 0 7 0 1 0 1 1 0 0 0 2 0 39 1 1 2 10 25 14 0 0 4 0 3 0 12 1 0 3 101 1 13 4 0 3 3 0 2 61 0 0 1 33 8 0 15 0 13 2 4 9 37 29 10 1 7 112 2148 9 1 55 10 4 0 0 7 1 6 5 10 0 1 0 48 1 1 0 2 3 0 0 0 0 28 1 0 0 7 22 7 0 5 0 2 1 2 3 0 12 0 2 0 0 5 24 16 32 1 4 3 6 0 1 2 5 4 7 0 1 0 37 1 0 1 0 0 98 1 20 0 2107 1 0 3 23 0 15 0 11 5 6 11 30 0 2 400 2 10 2 0 0 0 13 2 69 22 55 0 0 0 1 154 Bacteria;unclassified;unlassified;unclassified;unclassified;TM7_genera_incertae_sedis;uclassified
35 | 35 12 5 6 8 12 4 79 14 11 7 10 13 2 18 16 23 1 4 4 13 46 6 13 40 2 5 5 24 9 22 8 76 6 57 3 7 23 405 36 23 29 4 6 10 5 1 720 13 7 7 18 12 11 45 3 28 9 18 31 34 0 1 6 0 6 6 1 9 15 4 5 12 7 14 10 10 5 8 24 16 5 8 8 4 21 9 12 23 33 14 4 495 13 3 6 8 46 0 14 0 5 0 12 12 5 44 1 22 4 9 2 12 6 1 4 6 3 11 9 2 16 6 7 2 33 2 109 23 15 10 4 6 3 15 9 39 115 10 13 1 82 5 5 2 1 2 1 72 5 22 7 4 24 4 8 7 2 8 7 13 6 2 53 4 3 16 4 3 5 5 6 162 15 16 1 9 54 16 40 489 10 19 90 24 9 16 8 5 18 20 1 15 3 49 0 4 13 7 7 5 3 2 14 19 7 20 5 249 4 7 9 14 9 4 4 18 13 20 10 5 1 10 13 2 1 11 5 0 4 20 22 14 40 5 4 1 2 26 13 3 5 3 5 11 1 5 21 10 9 2 16 8 12 24 2 2 6 17 21 2 10 7 10 10 4 1 13 21 6 9 626 36 7 4 6 0 2 1 3 16 3 70 15 1 28 1733 16 6 1 4 5 3 6 7 12 6 5 Bacteria;Firmicutes;Negativicutes;Selenomonadales;Veillonellaceae;Veillonella;montpellierensis
36 | 36 0 2 14 3 2 737 1 0 39 0 29 4 9 1 18 142 6 29 10 36 23 1 26 5 48 1 17 4 1 2 109 7 2 9 18 0 6 2 8 0 7 1 14 1 2 6 7 0 0 0 0 1 1 14 5 1 11 9 16 15 14 1 15 9 3 0 2 3 3 1 6 13 2 5 3 1 25 0 28 6 2 19 0 16 4 0 4 0 0 8 496 6 11 566 0 23 7 8 0 0 13 2 0 28 11 0 2 1 0 1 5 0 3 0 0 14 1 7 2 40 56 46 0 2 1 0 0 4 24 5 2 492 7 0 2 1 1 0 3 2 2 23 11 0 0 18 7 51 1 3 1 104 25 3 0 3 11 5 7 1 9 0 2 58 18 18 4 1 0 0 6 0 4 2 6 27 0 60 2 22 12 11 19 0 5 8 2109 11 2 1 0 300 374 4 4 52 1 1 25 1 0 23 11 1 73 3 16 0 54 13 2 0 0 11 31 5 9 1 13 0 1 0 0 21 19 0 18 17 7 1 3 2 3 2 32 10 11 1 0 34 2 41 1 8 0 2 0 1386 35 1 0 1 13 7 0 23 11 16 5 336 3 2 5 2 19 50 1 1 2 3 5 3 2 28 1 0 1 17 22 1 18 0 1 1 14 0 1 15 12 47 3 3 1 3 15 1 50 Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;unclassified;unclassified
37 | 37 4 6 6 12 13 14 37 14 2 2 15 1 3 29 16 54 8 1 2 12 1 2 28 1 3 40 17 2 2 0 11 885 3 974 7 17 12 4 0 17 19 11 0 10 0 4 3 14 2 3 21 4 2 23 135 1 3 4 15 3 4 2 1 6 3 0 44 61 10 3 9 5 10 4 4 19 10 2 6 11 11 5 59 2 6 11 105 4 3 116 83 5 8 0 262 15 0 6 11 10 10 13 1 7 1 28 2 39 4 1 96 1 3 9 321 1 18 6 8 10 2 3 16 1 82 2 0 12 5 7 1 14 0 19 4 9 4 4 7 2 5 0 7 56 2 1 2 6 2 0 860 3 9 6 3 8 19 88 3 5 1 3 2 7 4 56 2 16 1 4 4 1 1 359 25 4 7 0 2 756 6 4 0 17 12 4 2 12 6 18 7 0 3 6 3 2 7 1 1 3 1 5 30 1 3 4 1 138 1 1 96 15 74 158 0 3 3 3 0 2 4 21 0 1 138 79 1 2 5 3 19 21 1 15 7 0 9 13 4 0 7 3 7 1 0 12 2089 21 18 10 9 13 3 0 15 1 24 1 56 0 55 0 98 33 2 7 4 3 0 10 1 12 1 7 1 6 3 4 7 2 7 10 3 6 5 11 11 8 1 0 1 38 24 11 3 17 2 Bacteria;Proteobacteria;Gammaproteobacteria;Enterobacteriales;Enterobacteriaceae;Escherichia/Shigella;unclassified
38 | 38 0 0 0 1 16 2 5 1 46 2 0 0 0 1 0 69 0 6053 0 2 1 0 5 0 0 1 8 5 0 0 2 14 0 1 0 1 0 0 0 42 1 1 0 30 17 0 0 0 0 1 1 0 1 1 1 1 0 0 1 5 0 0 0 1 1 1 1 2 8 1 7 3 11 0 4 0 2 0 5 2 0 1 1 0 2 0 0 2 1 0 3 0 8 41 4 2 0 1 4 11 31 1 0 0 1 16 0 0 0 0 37 1 103 1 0 3 0 1 14 19 35 47 2 3 0 1 0 1 0 0 0 0 1 14 1 3 0 50 2 1 3 3 1 0 1 1 1 60 125 0 1 0 49 0 0 2 7 0 2 0 0 0 1 1 1 5 1 11 0 10 0 2 1 1 0 1 0 44 0 0 0 1 3 1 0 0 42 1 1 0 790 45 22 20 0 24 0 2 2 2 1 6 0 1 0 0 1 0 35 0 0 2 23 4 3 2 0 1 0 7 0 11 0 29 2 11 1 0 1 1 0 2 0 10 0 171 12 3 8 52 2 33 0 1 2 17 6 1 0 17 50 0 5 0 1 21 0 0 2 2 1 1 0 13 0 1 1 1 0 1 2 0 52 31 0 5 0 2 2 0 22 1 0 0 0 1 6 0 9 49 0 0 1 0 2 3 50 Bacteria;Actinobacteria;Actinobacteria;Bifidobacteriales;Bifidobacteriaceae;Bifidobacterium;unclassified
39 | 39 1 4 0 0 1 0 22 219 0 4 11 0 2 1635 18 4 1 0 12 0 37 7 3 0 11 1 0 25 9 0 0 0 7 8 1 13 2 1 2 17 1 56 0 0 0 13 0 0 6 278 13 3 12 0 32 50 2 5 37 0 9 0 8 15 1 2 6 7 1 6 0 0 8 0 11 32 0 1 0 13 5 3 27 12 23 15 20 0 2875 49 0 0 1 2 5 1 0 2 0 0 2 36 12 0 0 5 11 31 16 0 6 6 22 1 3 2 3 29 0 0 3 3 4 2 0 7 0 1 9 0 8 1 7 0 2 1 3 1 0 2 6 0 1 12 415 0 7 0 1 0 9 2 4 0 10 6 0 4 4 0 5 1 0 65 16 1 3 1 2 2 3 5 1 20 573 0 17 22 0 1 0 3 0 1 13 0 7 1 0 23 4 3 3 1 4 2 5 1378 0 0 1 7 22 1 0 4 13 13 2 0 5 1 1 5 8 1 8 1 1 8 10 3 0 74 9 9 5 10 0 11 12 14 6 4 15 0 5 2 9 0 34 1 0 0 8 2 13 1 0 0 2 0 0 8 13 5 1 2 2 0 4 0 3 0 5 28 0 1 0 15 0 0 1 1 21 0 3 0 1 19 0 3 4 19 3 14 256 0 6 0 5 2 0 4 0 271 1 Bacteria;Firmicutes;Clostridia;Clostridiales;Clostridiaceae1;Clostridiumsensustricto;sp.
40 | 40 4 4 1 9 75 24 17 12 12 5 3426 29 2 640 9 8 42 0 15 60 128 18 14 1 22 5 2 10 0 6 5 9 3 836 14 9 4 14 5 5 5 20 6 3 2 1 246 2 25 3 35 32 29 3 16 17 3 36 89 13 1 6 48 1 3 0 2 13 5 2 6 3 16 11 2 56 18 58 108 13 7 5 19 2 57 11 9 25 12 48 1 2 4 1 27 23 3 1 1 20 17 92 52 28 0 3 0 38 3 59 1 37 9 6 206 23 4 33 7 2 49 1 0 7 44 3 1 2 24 3 3 22 1 139 44 47 15 6 5 35 1 2 12 7 4 4 0 4 4 5 60 2 0 2 4 57 12 0 3 3 3 31 4 18 8 313 7 4 0 1 43 6719 4 2174 1 52 27 1 28 464 2 0 1 3 18 8 1 4 24 24 0 0 1 43 1 29 12 10 1 5 0 12 11 42 0 4 4 540 1 13 38 4 11 1 3 2 2 76 3 0 79 3 3 1 1 113 3 1 10 4 42 21 6 28 0 3 17 1 88 2 51 3 5 1 18 9 9 30 42 0 4 4 12 4 12 1 9 20 156 4 10 0 5 19 4 20 1 27 2 1 4 14 33 4 112 4 43 16 16 3 3 124 55 12 19 84 34 6 2 1 26 0 7 26 2 8 0 Bacteria;Firmicutes;Bacilli;Bacillales;Paenibacillaceae1;Paenibacillus;unclassified
41 | 41 22 7 4 4 1 73 81 11 11 2 13 9 5 15 4 109 2 11 15 22 51 5 5 76 9 90 150 6 5 55 29 4 6 16 5 9 18 39 12 7 254 2 156 3 10 6 65 14 0 8 88 6 4 1 10 16 10 0 15 41 72 7 3 10 9 22 8 16 9 3 3 26 3 9 5 8 18 4 8 77 6 13 12 21 11 12 16 6 6 21 22 14 2 22 5 9 213 166 3 3 11 7 0 13 19 4 13 959 4 6 7 0 8 5 2 4 1 8 3 8 104 18 0 10 3 1 4 18 15 4 163 218 117 5 10 8 2 165 9 1 6 5 2 4 2 4 8 15 7 9 6 17 9 3 2 10 5 11 22 14 6 2 11 9 122 9 8 10 4 3 3 6 5 19 15 8 2 20 32 9 89 6 3 11 1 33 102 28 18 18 6 86 10 8 50 117 213 8 3 43 12 4 9 105 18 3 6 19 11 29 1 9 8 70 4 18 103 9 12 7 1 2 11 5 43 6 10 100 418 7 13 17 19 3 5 4 3 2 16 13 2 5 5 42 2 7 6 382 8 4 2 6 4 5 10 18 10 94 20 7 10 40 13 8 3 193 6 5 4 10 14 13 11 6 11 8 2 11 13 13 83 6 5 52 5 14 2 4 4 12 2 40 15 20 57 8 7 Bacteria;Firmicutes;Clostridia;Clostridiales;Clostridiales_IncertaeSedisXI;Parvimonas;unclassified
42 | 42 0 1 0 0 2 19 0 28 1 0 3 0 0 16 11 1 0 61 0 9 0 244 21 0 14 2 0 0 1 1 1 0 2 17 8 23 0 1 1 4933 1 0 3 24 32 1 0 13 0 4 22 0 3 0 0 0 0 0 2 1 0 52 0 0 0 0 2 0 0 0 0 0 0 0 0 0 12 0 12 28 18 0 100 0 1 10 18 3 0 2 0 1 0 0 1 18 1 0 1 2 71 3 10 8 0 0 0 25 21 1 0 0 19 3 1 0 0 1 0 1 0 1 1 0 0 0 0 1 9 0 0 14 0 0 0 0 0 49 0 0 1 0 1 4 1 1 0 2 38 38 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 2 1 1 0 0 0 0 0 1 0 21 0 0 3 13 0 0 0 0 1 0 0 1 0 22 1 0 0 0 1 0 0 1 29 1 1 6 29 1 0 11 1 249 1 1 0 0 1 2 1 0 0 2 0 1 0 0 27 1 1 0 0 0 2 0 22 21 0 0 1 1 0 0 1 0 26 0 0 0 0 0 15 14 4065 19 39 0 0 1 164 0 1 3 0 0 1 0 2 0 1 0 0 1 0 25 0 1 3 2 0 2 0 10 11 0 1 2 0 1 8 36 0 3 0 1 0 1 0 0 0 12 32 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;unclassified
43 | 43 3 7 0 16 22 50 35 24 4 20 72 4 3 48 36 0 5 5 1 47 43 1 22 2 168 1 58 19 29 2 7 32 4 20 62 50 2 16 4 30 29 70 2 35 6 1 2 38 3 8 75 10 2 1 58 14 2 13 44 0 3 110 5 10 22 0 9 12 1 5 44 9 83 2 11 59 80 10 18 29 25 0 177 12 54 19 117 29 36 73 0 39 2 0 4 35 2 8 19 55 31 118 10 54 7 12 5 38 29 1 43 5 60 16 5 3 2 87 38 2 2 8 7 38 46 3 0 57 13 29 9 19 4 60 3 22 2 3 4 3 4 1 26 4 3 0 7 3 192 3 34 4 2 23 1 37 36 26 1 20 182 6 34 43 52 4 6 18 5 55 18 5 4 55 3 32 7 0 1 23 25 21 4 245 96 7 3 579 15 39 14 1 1 93 4 4 37 48 2 5 2 7 48 3 1 11 24 33 6 1 8 136 41 24 4 8 2 21 0 4 104 578 3 1 13 3 24 6 0 12 18 92 5 49 10 2 28 17 6 3 99 2 2 1 15 57 20 24 43 51 46 24 2 3 31 0 12 1 1 1 1 2 4 43 14 37 41 5 2 40 2 50 20 1 87 46 11 28 40 5 31 2 7 57 26 22 7 19 0 2 3 2 9 9 3 11 1 Bacteria;Firmicutes;Bacilli;Lactobacillales;Lactobacillaceae;Lactobacillus;unclassified
44 | 45 15 14 3 4 1 1 1 12 19 0 1 2 2 1 5 22 1 16 26 6 13 19 0 15 1 320 40 12 0 15 39 2 15 3 3 1 1 20 6 2 7 5 3 2 9 5 13 0 0 18 1 0 10 1 11 2 3 0 8 7 13 2 2 15 10 10 20 5 3 12 0 3 7 14 6 16 2 0 0 7 0 5 2 21 9 2 5 3 44 15 11 1 0 34 9 3 4 345 0 2 1 7 0 1 10 0 10 57 21 9 4 8 10 3 11 4 11 8 4 9 11 18 10 0 5 9 9 1 13 0 1 5 14 3 0 0 0 97 4 1 8 1 0 19 3 1 18 22 0 3 3 117 6 2 11 0 0 1 4 2 3 2 2 8 23 5 13 3 8 2 0 1 4 18 16 0 10 954 13 0 32 3 6 1 2 8 150 1 11 1 5 43 19 6 19 10 0 1 2 1 13 1 0 15 4 15 4 5 14 42 11 5 3 3 6 2 0 0 10 0 0 2 18 5 7 6 4 26 10 13 1 3 11 3 1 3 6 0 0 15 6 5 4 14 0 1 2 1 0 2 2 3 0 12 1 14 5 96 4 3 8 335 7 8 0 385 1 0 13 16 1 3 3 9 7 1 5 6 5 19 99 12 5 7 0 3 1 5 0 10 9 371 3 0 1 1 12 Bacteria;Firmicutes;Clostridia;Clostridiales;unclassified;unclassified;BVAB3
45 | 46 2 7 36 11 6 18 0 6 57 3 11 7 2 3 10 44 1 10 11 13 31 47 8 14 20 76 8 9 1 111 18 159 5 42 11 6 8 14 11 7 84 23 9 8 2 9 17 18 1 9 16 47 4 112 3 12 8 36 6 12 9 6 2 11 4 8 3 7 6 1 8 9 5 10 6 3 16 10 8 6 1 556 5 14 111 0 4 23 5 3 18 23 2 9 3 10 8 204 5 144 62 2 5 79 13 1 4 3 8 0 4 4 3 2 2 8 29 26 6 9 19 25 1 13 19 2 1 3 5 7 16 13 5 28 1 455 6 12 11 2 6 83 6 4 10 4 4 31 4 6 9 8 3 5 2 2 3 4 7 19 14 0 13 28 4 7 12 6 2 4 7 1 26 22 5 8 5 12 60 603 28 20 174 19 5 12 248 5 8 5 2 21 5 15 4 11 7 6 9 2 1 6 7 12 9 2 11 5 530 7 1 11 5 5 15 3 3 9 11 11 0 4 7 3 12 4 15 9 2 40 5 2 9 4 29 8 6 1 9 72 6 7 1 2 0 23 1 174 18 6 3 12 11 17 55 6 5 24 168 15 71 57 96 6 1 5 6 8 5 5 18 227 7 40 25 9 3 9 12 90 6 4 2 0 5 3 0 5 8 13 2 9 4 3 7 2 17 Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae;Peptostreptococcus;anaerobius
46 | 50 6 1 12 6 2 9 0 10 14 5 10 0 5 10 18 3 3 7 3 14 92 0 3 0 8 20 1 11 0 0 25 1 0 19 5 3 0 4 1 9 4 1 1 2 4 2 8 0 0 0 19 0 0 6 0 0 22 0 0 27 39 12 0 2 0 9 1 1 0 0 0 2 1 0 0 1 6 0 10 17 6 0 11 0 2 3 7 0 2 2 18 0 7 0 0 3 0 40 0 0 10 0 0 7 0 1 2 1320 0 0 0 1 1 3 0 11 0 1 0 12 3 5 0 3 0 4 0 1 4 1 0 7 1 0 1 0 0 4 4 0 0 7 0 0 0 4 0 6 427 1 0 0 1 0 0 3 4 0 13 0 0 0 1 5 1 17 1 2 0 0 0 0 0 10 2 8 0 1 2 1 2 0 9 1 1 0 167 2 12 5 10 11 0 1 2 3 1 1 20 0 0 14 10 0 1 1 4 9 1 0 0 0 0 3 15 0 0 3 0 9 0 1 0 0 0 2 2 8 6 5 6 4 2 0 2 4 1 0 16 2 1 1 3 0 2 0 4 1249 6 0 4 0 10 1 2 18 5 5 2 10 0 0 30 10 0 1 0 1 1 6 1 4 7 2 2 0 0 3 6 74 1 13 3 0 2 38 0 2 961 0 0 0 6 0 14 16 1 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;sp.
47 | 51 7 3 6 7 10 2 2 6 6 4 3 5 0 8 7 2 7 0 10 1 0 5 6 6 4 3 14 8 3 112 8 54 3 51 7 5 1 2 3 160 27 14 4 1 4 0 1 0 3 0 9 8 1 3 1 6 3 15 11 0 10 7 23 11 1 8 1 3 1 2 9 3 10 7 37 30 0 4 1 6 3 7 3 9 81 3 6 2 2 3 1 2 3 1 3 12 3 10 5 35 5 1 6 51 1 4 0 3 3 6 29 2 9 5 4 2 2 8 14 3 5 10 2 3 3 1 1 2 5 1 1 5 13 1622 0 90 0 2 10 0 5 2 2 3 10 4 3 7 60 2 7 2 0 1 1 1 10 1 0 3 7 3 9 4 1 4 4 19 5 4 3 1 4 6 3 6 4 0 410 187 0 2 2 14 1 9 3 14 3 14 4 1 0 150 5 0 1 16 4 8 11 4 7 8 0 0 4 41 1 6 1 11 18 3 1 3 1 11 2 4 2 5 6 1 1 1 8 2 3 7 9 12 97 11 4 9 11 3 16 2 4 1 3 2 1 12 6 10 5 17 14 4 3 4 21 2 10 0 9 0 7 6 0 11 3 12 4 4 6 5 3 4 14 8 35 3 7 2 3 14 20 0 0 3 18 21 1 3 2 6 1 5 10 5 6 7 3 Bacteria;Firmicutes;Clostridia;Clostridiales;Clostridiales_IncertaeSedisXI;Finegoldia;magna
48 | 52 6 4 28 13 14 2 5 8 8 0 3 2 2 10 10 70 2 3 6 5 30 7 2 23 4 8 79 3 2 128 14 64 7 15 5 9 3 4 5 5 137 9 40 6 5 6 3 8 1 2 11 21 3 8 4 4 2 44 11 2 22 15 47 12 7 5 1 4 1 4 9 19 11 4 18 16 6 5 2 11 1 6 7 13 38 0 9 2 4 9 10 8 1 15 2 19 5 23 7 28 5 5 4 41 3 6 4 14 1 5 9 0 8 10 3 4 0 12 9 85 59 6 3 15 4 2 1 3 2 2 6 6 13 1425 5 46 1 6 5 7 1 5 14 0 3 4 12 13 426 1 5 2 4 0 1 14 17 3 0 5 11 5 27 7 24 4 16 16 5 5 10 8 7 5 7 1 8 13 204 7 4 1 3 18 2 4 6 4 6 23 8 23 3 173 15 15 24 22 2 9 7 2 12 2 3 2 11 39 11 24 5 18 14 42 2 7 0 6 1 12 3 7 8 1 5 2 14 25 7 14 8 7 8 11 8 8 9 2 22 9 2 4 5 15 3 18 5 10 6 16 12 7 4 3 112 3 17 5 21 4 5 31 13 8 5 20 2 7 4 5 7 24 9 14 29 10 3 1 9 10 37 2 4 3 9 101 3 2 0 5 1 9 13 8 4 6 8 Bacteria;Firmicutes;Clostridia;Clostridiales;Clostridiales_IncertaeSedisXI;Peptoniphilus;unclassified
49 | 53 0 0 0 0 16 0 0 3 0 2 1 0 0 0 0 0 0 1 2 0 0 0 0 0 0 1 15 0 1 0 0 12 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 17 0 33 13 0 0 0 2 1 0 0 1 1 0 0 0 0 0 0 1 0 0 0 25 0 6 0 18 0 0 0 0 0 0 1 0 0 2 12 0 1 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3256 0 0 0 0 17 0 0 0 0 0 0 0 0 11 0 1 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 24 0 10 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 79 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 1 0 10 16 0 0 0 0 1 0 1 0 17 0 0 0 0 0 0 0 0 0 25 1 12 2 12 16 0 0 0 0 0 0 0 0 22 0 0 0 26 17 1 1 0 0 0 0 0 0 0 0 0 0 19 1 1 0 0 0 0 0 1 2 0 0 16 0 0 0 0 24 0 0 1 0 0 0 0 0 0 0 0 0 9 0 0 0 Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Corynebacteriaceae;Corynebacterium;glucuronolyticum
50 | 54 0 2 8 8 2 7 2 14 0 0 102 1 2 12 4 2 2 0 4 19 0 5 8 0 5 2 6 0 0 0 2 1 3 1102 5 9 0 4 1 11 1 0 0 1 0 2 2 1 0 3 23 1 3 0 0 0 3 4 12 2 0 2 0 1 2 0 1 6 2 1 7 0 18 5 6 14 9 1 7 16 3 0 7 1 4 4 5 0 1 6 2 0 1 0 21 26 0 3 0 9 9 1 0 21 0 2 0 10 7 62 3 0 2 2 101 6 0 1 6 4 0 0 1 1 7 2 0 1 7 4 0 5 0 687 1 1 0 0 3 0 0 3 2 2 0 1 3 1 1 3 1 0 0 0 2 0 11 0 0 0 0 2 1 2 0 156 3 8 1 3 0 0 0 27 0 10 2 0 8 1044 1 0 1 2 3 1 0 1 4 19 2 0 0 19 1 1 0 0 4 0 3 7 15 1 1 5 0 22 0 2 0 3 7 0 4 0 0 1 0 0 0 1 4 0 1 1 1 0 3 0 39 11 1 6 1 4 7 0 10 0 3 1 4 0 0 7 4 17 12 1 5 1 2 1 7 0 7 0 19 2 0 0 2 11 3 2 3 1 3 7 0 1 1 1 35 10 0 2 11 0 8 139 0 3 4 10 0 3 2 1 0 1 13 5 1 3 0 Bacteria;Firmicutes;Bacilli;Bacillales;Bacillales_IncertaeSedisXI;Gemella;unclassified
51 | 56 5 3 2 4 11 4 37 1 2 2 0 4 3 0 3 201 0 5 7 1 42 0 0 163 0 96 21 1 0 59 154 3 2 2 1 1 0 0 14 2 12 2 55 4 6 1 8 2 0 1 0 1 3 2 6 1 80 0 17 7 149 2 0 6 3 0 1 7 3 1 1 5 1 4 3 1 8 0 5 9 0 20 0 19 5 0 4 4 3 5 9 3 2 7 2 1 9 17 0 0 0 2 0 0 2 2 6 2 1 1 5 1 4 3 1 0 0 5 13 3 241 33 0 4 2 0 2 8 0 3 3 6 522 40 4 3 0 7 5 0 4 4 5 4 1 2 6 3 281 7 0 2 0 3 2 5 2 3 5 4 2 2 2 4 3 4 13 1 1 0 1 0 3 2 7 1 0 28 33 1 234 0 4 0 1 22 109 5 4 0 1 26 0 32 12 13 2 3 2 1 3 0 3 405 11 1 5 5 26 8 2 0 5 11 4 8 8 13 5 0 1 2 9 9 5 1 10 20 5 1 3 1 8 1 1 2 1 0 2 2 0 3 2 10 0 0 1 0 0 2 3 8 3 5 2 4 2 27 21 3 21 23 485 0 0 226 1 2 4 6 13 2 3 2 6 1 2 2 0 0 21 1 0 5 0 7 1 0 1 4 1 35 2 1 68 1 4 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;unclassified
52 | 57 7 3 1 1 0 0 0 0 9 1 0 0 0 0 2 31 0 7 18 1 2 19 0 17 3 227 0 8 0 2 1 0 5 1 1 0 0 5 1 1 1 3 4 0 3 1 4 0 0 6 7 1 4 1 4 18 5 0 2 4 24 0 0 10 4 2 5 11 1 7 0 1 0 1 9 9 1 0 1 2 0 0 0 19 25 0 2 2 0 7 8 0 0 10 14 4 0 647 0 0 0 0 0 0 2 1 7 5 5 2 2 0 2 0 3 1 0 4 0 7 13 13 2 2 3 1 1 1 0 0 0 2 12 3 2 23 0 1 9 0 3 2 2 6 2 2 18 8 1 2 1 5 6 0 3 3 1 1 0 0 1 1 0 5 7 8 13 6 1 0 0 1 1 8 14 5 5 13 5 0 2 0 3 0 0 3 33 1 7 0 4 8 5 5 41 5 0 0 1 2 7 1 0 3 1 6 0 7 8 9 2 2 4 0 2 1 0 0 6 6 0 0 2 2 15 4 0 77 2 1 0 5 14 0 0 2 0 0 2 1 5 3 3 2 1 0 0 1 0 1 1 2 0 0 0 4 1 9 0 14 4 6 14 1 0 139 3 0 1 2 3 4 1 1 0 0 1 0 1 0 3 5 2 3 1 4 1 0 0 6 6 32 0 2 47 0 5 Bacteria;Firmicutes;Clostridia;Clostridiales;Lachnospiraceae;Moryella;bacterium
53 | 58 0 1 0 14 1 15 0 2 16 10 0 0 0 0 0 6 2 7 0 2 51 1 0 0 0 0 9 3 0 50 2 17 12 1 0 1 0 1 28 0 1 4 0 9 0 1 0 26 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 14 1 0 1 0 1 0 1 5 0 1 0 21 0 0 0 19 1 5 9 2669 0 10 0 2 0 0 15 0 21 0 0 0 0 0 0 0 0 1 1 2 0 1 0 0 0 56 2 34 10 200 0 2 11 0 1 1 2 14 2 6 0 2 1 13 0 0 0 0 1 1 1 0 0 1 1 15 6 0 19 0 10 8 0 1 0 14 0 18 26 0 0 0 0 22 0 0 0 0 14 1 0 3 1 0 1 15 19 1 10 17 0 32 0 0 12 6 0 0 0 19 4 2 0 10 9 5 0 1 2 3 17 4 0 1 2 1 1795 0 1 17 2 1 1 1 0 1 0 1 0 0 1 6 0 0 24 0 21 0 0 0 1 0 0 1 0 0 0 9 1 13 0 0 0 4 0 0 2 2 3 7 2 0 1 11 0 0 0 0 1 0 0 6 0 5 11 1 0 0 0 9 3 12 0 50 2 0 0 55 1 0 0 2 0 2 0 0 0 19 0 1 0 0 0 0 17 Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium;unclassified
54 | 59 1 2 0 1 3 6 7 0 0 1 1084 2 1 12 2 5 2 0 63 6 3 41 8 0 6 1 2 3 5 1 1 4 0 132 5 0 1 0 5 2 3 2 0 1 1 0 5 1 1 3 64 3 0 1 0 54 1 1 61 0 2 1 0 6 1 0 0 0 3 2 4 2 6 0 5 17 6 0 15 5 3 0 4 0 125 2 3 84 2 3 0 2 1 0 2 14 1 3 0 3 5 12 2 2 0 2 0 3 0 8 5 0 1 1 30 3 0 1 6 0 1 1 0 4 13 1 1 3 6 0 2 10 0 530 0 0 0 0 4 0 0 1 2 2 1 0 0 0 1 1 5 3 1 1 1 13 1 1 0 3 0 3 5 5 1 26 14 4 1 4 1 1 2 2 1 99 3 0 9 13 1 1 0 1 0 2 0 2 1 3 2 0 1 87 0 1 35 5 0 2 1 3 2 1 1 0 2 80 0 17 0 5 2 2 6 5 2 2 1 1 4 1 0 0 0 1 0 1 1 2 18 9 0 12 1 4 8 0 16 0 39 0 1 0 2 5 1 7 18 6 5 10 9 0 3 0 1 60 24 0 3 1 0 3 1 3 1 2 1 1 1 0 100 3 34 2 2 8 6 2 3 11 0 0 5 1 3 2 1 0 0 0 1 4 2 0 0 Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;unclassified
55 | 62 27 1 0 7 25 11 6 5 0 1 8 5 1 220 2 4 5 2 1 8 6 3 84 4 8 1 9 0 131 4 0 6 8 8 13 4 3 3 2 2 1 7 0 0 1 4 0 0 1 11 5 3 108 0 7 4 0 2 8 0 0 5 1 0 8 0 3 5 2 2 5 0 2 1 1 0 3 2 9 1 3 0 4 1 234 1 2 4 2 11 0 2 1 1 0 11 1 0 1 4 7 10 2 14 0 4 1 6 5 0 3 2 2 1 7 1 2 2 473 3 3 0 1 1 6 1 1 7 8 5 3 7 1 3 3 1 0 0 0 1 2 2 3 528 2 0 0 0 2 1 5 0 3 1 4 8 12 60 0 3 6 0 2 3 7 2 1 1 91 8 1 0 1 2 0 3 9 0 2 285 2 3 1 3 9 0 0 0 2 2 1 2 0 1 0 1 2 7 1 1 1 2 7 2 0 3 2 11 1 3 5 0 122 2 0 1 2 3 0 0 4 3 1 0 3 4 4 1 3 4 4 1 0 9 5 1 3 96 0 0 1 2 4 0 2 7 2 23 8 6 4 0 1 1 3 0 11 0 0 0 1 1 0 2 1 8 1 2 2 3 2 3 1 2 2 5 0 3 8 2 6 5 1 1 6 2 1 2 0 116 3 2 2 0 0 25 4 Bacteria;Firmicutes;Bacilli;Lactobacillales;Lactobacillaceae;Lactobacillus;coleohominis
56 | 63 3 0 13 0 0 1 0 3 1133 0 3 0 8 2 4 7 0 8 1 15 1 2 4 0 1 1 0 0 0 0 21 4 0 113 0 1 10 13 0 2 1 42 1 2 0 0 6 1 0 0 308 2 0 364 1 3 0 1 1 31 1 3 0 0 15 1 0 0 0 0 1 6 0 5 0 1 5 2 2 5 9 0 15 0 3 4 0 1 4 0 13 0 6 14 0 2 0 0 0 2 126 2 2 3 9 0 1 13 0 0 1 2 6 1 0 19 1 3 1 10 10 5 0 5 1 0 0 0 5 0 0 4 1 0 1 6 1 0 0 0 0 15 0 0 0 12 0 12 7 1 0 3 9 1 0 4 0 0 0 0 0 0 0 0 12 22 2 1 0 0 0 0 2 27 0 10 0 13 0 40 10 2 1181 1 1 0 2 0 15 9 0 8 17 2 2 13 0 0 45 3 0 0 4 0 1 0 0 6 12 1 0 0 0 0 9 0 0 1 10 0 1 0 1 1 0 1 0 0 1 3 4 5 0 1 0 15 1 0 0 11 5 7 1 2 0 1 0 4 182 2 2 0 22 1 5 6 1 1 0 15 0 4 0 4 0 0 0 0 0 9 0 7 8 49 1 1 0 14 3 7 0 0 3 0 0 3 0 10 10 9 4 0 0 0 19 2 13 Bacteria;Actinobacteria;Actinobacteria;Bifidobacteriales;Bifidobacteriaceae;Alloscardovia;unclassified
57 | 64 1 2 8 6 0 1 0 3 12 1 0 0 1 0 0 6 8 3 0 0 13 0 0 1 0 4 0 0 1 30 7 4 0 10 0 0 0 2 0 0 710 1 0 5 5 0 0 1 0 1 1 2 0 0 0 0 0 0 3 7 4 8 0 1 12 0 1 1 0 0 0 8 0 0 1 0 1 1 0 3 0 0 0 1 1 0 1 2 3 0 2 1 1 4 0 1 0 0 1 0 0 2 0 0 0 6 0 1 0 1 0 2 0 8 0 0 0 1 1 953 8 14 1 5 1 2 1 3 2 0 5 3 0 0 0 0 0 0 0 0 2 6 10 0 1 1 1 9 9 0 1 0 4 1 0 19 7 2 0 0 0 0 2 3 2 4 2 4 1 0 0 0 0 1 0 0 0 48 13 0 1 0 2 1 0 3 11 8 17 0 0 10 2 0 2 18 0 0 1 1 0 1 2 3 0 0 2 0 9 2 0 1 0 10 1 12 0 6 1 2 0 0 4 3 1 0 10 4 207 4 2 0 0 0 0 3 0 1 18 4 0 5 6 29 1 0 1 7 0 0 0 2 0 3 0 2 12 0 1 1 0 3 0 1 0 4 2 2 1 0 0 36 15 10 1 0 1 0 0 131 3 0 0 3 0 2 0 0 19 7 0 4 10 0 24 0 11 Bacteria;Firmicutes;Clostridia;Clostridiales;Peptostreptococcaceae;Peptostreptococcus;unclassified
58 | 65 2 0 0 0 0 0 1 7 4 1 0 3 1 0 0 25 0 2 3 0 64 1 0 2 0 30 15 1 0 5 6 0 0 0 0 5 0 2 6 0 2 0 9 1 6 0 38 0 0 0 1 1 1 0 2 9 21 0 1 1 1 0 0 0 0 4 0 2 5 0 0 0 2 9 0 1 0 0 0 0 0 7 1 0 7 0 0 0 14 5 2 0 0 5 0 0 1006 8 0 3 0 0 0 0 1 0 0 0 0 2 1 9 3 0 0 1 0 1 0 2 10 5 0 1 0 0 3 2 4 0 0 1 0 2 0 0 1 10 14 4 2 5 1 1 0 1 1 19 1 7 0 1 2 0 2 0 0 0 5 2 1 0 9 1 2 0 0 0 0 1 0 1 12 2 1 0 0 170 3 0 2 0 0 1 1 13 6 1 1 0 1 4 2 0 0 4 0 0 0 4 5 0 0 3 6 0 0 0 7 6 0 0 1 1 0 1 2 0 6 0 0 0 6 2 1 1 0 0 3 4 0 1 5 0 1 0 0 0 0 11 0 4 0 473 0 0 0 0 0 0 0 1 3 12 0 3 0 5 7 1 13 16 6 1 0 70 0 3 2 0 9 0 3 4 17 0 0 0 4 12 18 0 0 1 0 1 0 0 0 2 0 2 1 1 0 0 4 Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Arcanobacterium;sp.
59 | 66 1 0 0 0 1 0 1 14 4 0 0 0 0 0 0 1 0 0 1 1 187 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 8 0 0 0 4 0 0 1 0 2 0 0 0 1 6 0 2 3 9 0 0 0 3 2 0 0 1 0 0 0 3 0 0 0 0 13 0 7 0 0 0 1 0 0 0 0 1 0 0 2 0 7 1 190 0 3 0 3 0 0 70 0 0 0 0 0 0 4 0 1 0 0 0 2 3 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 6 9 0 0 0 0 1 0 3 0 0 1 0 1 1 0 0 0 0 2 1 0 0 0 0 1 0 4 1 0 1 0 1 2 0 0 0 1 3 0 3 1 0 1 0 0 2 8 1 0 52 0 0 1 0 2 0 0 0 1 8 2 0 0 0 0 0 1 1 0 0 10 5 1 0 0 1 0 0 0 0 0 0 1 2 0 6 2 0 1 0 0 3 0 0 0 0 10 0 0 0 0 9 0 1 2 0 9 3 0 4 1 2 1 0 0 7 0 0 0 0 0 0 0 2 4 21 1 2 0 0 0 0 0 0 1 1 6 2 0 9 0 0 0 52 0 0 1 0 0 0 0 1514 0 0 0 0 0 1 0 0 0 0 0 0 5 0 3 0 1 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;multiformis
60 | 69 2 0 27 4 3 0 0 10 15 2 0 0 4 2 1 2 4 1 0 0 8 0 1 0 0 0 4 1 0 0 14 8 1 6 0 0 5 3 1 3 6 0 29 3 2 1 0 1 0 0 4 0 0 254 7 0 2 0 1 12 0 3 0 0 4 0 0 0 1 0 4 9 9 3 1 0 0 0 0 44 3 0 3 0 1 0 1 0 2 0 12 0 7 5 1 0 0 0 0 2 5 0 0 0 1 2 0 20 1 0 98 2 6 4 2 11 0 2 1 5 1 2 0 4 0 0 0 1 5 0 2 0 0 4 1 0 1 0 2 0 0 7 1 1 0 3 0 1 293 0 0 2 4 2 5 1 9 0 0 1 0 1 6 0 0 19 0 2 0 3 2 0 1 0 0 1 0 6 0 0 0 0 33 0 0 0 1 3 4 0 143 0 7 5 1 0 0 0 10 6 0 1 3 1 5 0 1 0 2 0 0 0 4 2 10 1 0 6 0 2 0 2 0 0 0 2 4 0 2 22 2 3 0 1 0 13 2 1 3 0 1 0 5 1 1 3 1 2 0 5 4 1 12 7 42 2 19 1 0 11 0 0 1 6 1 0 0 2 0 1 0 0 4 76 0 7 0 0 0 7 5 1 3 0 0 1 0 1 10 0 0 0 7 0 10 3 1 Bacteria;Actinobacteria;Actinobacteria;Bifidobacteriales;Bifidobacteriaceae;Bifidobacterium;unclassified
61 | 70 2 4 0 0 5 4 1 4 2 0 0 4 0 0 1 5 0 5 1 0 4 1 0 5 3 0 774 13 1 6 32 1 4 1 2 0 0 0 4 0 7 2 170 0 5 0 1 0 0 0 3 1 1 0 5 3 1 0 6 2 3 0 0 1 3 3 0 0 0 0 5 0 5 4 1 3 0 0 0 6 1 0 0 8 12 0 1 4 18 3 63 6 1 3 0 0 1 1 0 4 0 10 1 1 1 0 2 0 0 2 5 4 5 1 1 2 0 13 5 1 0 5 0 0 0 0 1 0 1 0 0 1 3 5 0 0 0 2 0 1 1 3 0 0 0 3 0 2 0 0 0 0 1 0 3 0 6 1 1 0 6 0 2 6 8 3 1 0 0 1 3 0 1 5 0 0 0 453 10 0 1 4 3 0 4 7 5 6 0 0 2 3 0 6 80 0 0 2 6 5 3 0 5 1 1 0 3 0 6 141 0 0 8 0 4 0 1 0 1 0 0 2 7 1 6 0 8 143 3 1 0 0 1 5 0 3 7 0 1 0 8 0 0 1 0 6 1 0 0 6 5 5 4 3 0 0 0 4 1 28 3 152 1 10 1 792 1 2 0 2 5 0 1 3 8 6 2 1 2 5 435 0 0 6 0 0 0 0 3 1 1 5 0 0 1 0 3 Bacteria;unclassified;unlassified;unclassified;unclassified;unclassified_Bacteroidales;uclassified
62 | 71 0 0 6 0 1 9 7 0 0 0 279 1 2 5 2 4 0 2 7 12 1 1 4 0 8 4 0 0 0 2 4 1 2 100 7 0 0 0 2 3 0 1 2 0 1 0 0 0 0 6 0 1 2 0 0 1 10 10 7 4 0 1 1 0 1 1 0 10 2 2 10 0 4 0 4 10 9 0 19 2 0 0 2 1 0 0 1 0 1 6 2 0 2 0 0 18 0 0 1 2 9 0 1 13 0 1 0 1 0 3 1 0 0 1 79 3 1 4 2 0 0 0 0 1 11 1 0 0 8 10 0 7 0 214 1 0 0 0 0 0 0 5 9 5 0 2 6 1 1 1 0 1 0 0 0 1 2 0 0 0 0 0 1 0 0 506 1 2 0 1 0 1 1 2 0 22 2 0 7 1568 0 1 3 1 10 0 0 1 0 2 0 0 0 15 0 0 2 0 3 0 2 10 1 1 0 5 0 10 0 0 0 3 10 0 1 2 1 0 1 0 1 2 0 1 0 6 1 1 0 0 3 2 0 2 0 1 3 0 10 0 3 6 3 0 0 1 1 8 21 4 2 0 10 0 1 0 0 2 29 5 6 0 0 3 11 0 0 0 0 0 0 0 0 0 1 1 0 2 12 0 4 12 0 0 5 1 0 3 4 0 0 0 1 0 4 0 0 Bacteria;Firmicutes;Bacilli;Lactobacillales;Streptococcaceae;Streptococcus;unclassified
63 | 74 10 0 0 1 2 0 1 1 4 0 0 1 1 1 2 11 0 2 3 1 3 0 0 22 1 734 1 0 0 17 0 1 0 1 0 1 1 1 3 0 1 2 1 1 4 2 3 3 0 1 1 2 0 0 0 2 0 2 4 0 5 0 8 4 4 5 1 13 2 1 0 6 0 4 1 1 0 0 0 0 0 3 0 3 0 0 0 4 0 11 1 0 2 4 2 4 13 26 4 1 0 1 1 1 2 1 5 0 0 5 1 0 1 3 0 0 0 1 2 1 4 3 0 0 9 0 6 4 0 1 0 2 5 53 3 11 0 67 1 6 5 3 0 4 0 2 4 0 2 2 2 1 0 0 2 1 1 1 1 1 1 1 0 3 12 11 1 2 1 2 1 1 1 4 4 0 1 3 12 1 24 1 1 3 0 2 1 2 1 1 1 1 1 0 42 3 0 5 0 4 5 0 0 16 1 0 3 5 3 21 4 1 7 28 2 5 1 1 2 1 0 0 4 0 3 13 1 64 2 1 2 0 4 0 1 1 2 0 1 5 1 1 0 7 0 4 0 0 0 1 0 0 3 2 0 0 2 3 3 0 21 13 0 2 1 0 1 1 9 0 5 10 0 2 2 3 0 1 3 1 0 0 0 1 0 1 0 1 0 0 0 33 0 4 21 1 2 Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Mobiluncus;unclassified
64 | 80 4 0 0 1 2 18 2 0 5 0 11 1 0 2 2 0 3 1 12 8 10 1 4 14 13 3 1 3 0 168 2 1 1 9 6 3 1 13 2 1 188 3 0 1 2 0 3 0 0 1 1 2 0 1 2 0 1 3 4 2 12 2 0 13 5 3 0 1 0 0 0 4 0 9 6 9 16 3 12 86 2 37 2 10 0 0 0 0 0 3 3 9 2 3 2 10 0 313 1 7 6 0 0 8 4 1 4 1 0 4 0 0 0 1 0 0 1 14 2 1 3 4 1 3 1 0 2 9 4 1 0 9 15 8 1 1 2 0 1 0 3 1 3 1 0 0 3 2 1 0 1 2 2 0 0 2 4 0 0 0 2 0 3 9 4 1 10 5 0 0 4 0 2 3 7 6 1 3 63 8 0 1 1 5 1 3 79 3 6 4 0 9 1 0 6 1 0 10 0 0 8 8 6 7 2 5 6 2 6 10 0 3 0 1 0 1 0 3 3 0 0 1 13 3 0 0 10 9 42 1 0 3 8 0 4 0 1 0 3 1 1 1 1 5 0 3 2 740 15 1 0 0 1 0 0 0 5 5 0 0 0 225 0 2 0 2 0 2 5 1 2 5 3 1 2 0 1 8 7 3 1 5 1 2 8 0 0 5 1 2 3 4 47 2 5 4 1 Bacteria;Fusobacteria;Fusobacteria;Fusobacteriales;Fusobacteriaceae;Fusobacterium;unclassified
65 | 82 2 9 2 1 5 7 3 3 8 0 3 1 1 144 2 0 0 2 6 4 4 10 1 0 1 0 13 1 1 9 4 13 10 3 4 1 0 9 11 0 5 5 5 0 1 2 9 1 2 8 1 5 7 0 3 4 2 3 19 2 2 2 0 6 1 1 3 2 0 5 5 4 8 0 16 15 0 2 1 3 2 0 3 3 15 1 1 0 0 5 0 8 2 0 3 5 0 5 8 10 0 24 0 1 3 4 4 1 8 5 7 0 1 2 6 4 1 11 5 0 4 1 4 3 3 1 0 4 1 0 3 0 0 512 0 1 0 1 6 7 3 0 1 15 89 0 3 4 0 2 2 0 1 1 2 4 2 2 0 5 5 2 4 2 1 3 1 6 9 4 0 0 0 3 0 1 8 0 126 4 1 0 0 0 0 1 0 12 3 10 3 0 0 17 5 1 0 121 1 6 10 0 7 1 1 4 1 1 7 1 0 3 4 3 2 1 2 2 0 5 2 3 3 2 2 0 6 0 0 2 3 6 4 9 29 2 3 5 4 0 3 0 2 1 1 4 5 2 1 5 2 2 1 0 6 1 9 2 4 0 0 6 0 6 1 5 4 3 1 4 2 3 1 3 2 7 2 0 1 2 6 247 0 4 1 1 2 2 0 2 0 1 1 1 16 3 0 Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Corynebacteriaceae;Corynebacterium;unclassified
66 | 84 0 1 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 1 0 0 53 0 7 1 0 0 0 5 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 12 0 0 5 0 0 1 0 0 0 2 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 28 0 0 0 0 0 2 0 0 0 0 0 0 0 2 0 0 0 0 1 1 0 1 0 8 0 0 0 0 0 0 2 0 0 2 0 0 0 10 0 3 0 2 2 0 0 0 0 0 4 16 0 0 0 0 0 1 0 1 0 1 0 0 1242 1 0 0 0 9 3 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 5 1 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 1 5 0 0 0 0 0 0 8 0 9 0 4 0 0 0 0 0 0 0 0 7 0 0 5 0 1 2 0 0 0 0 0 1 7 0 0 0 0 0 1 0 0 0 0 14 0 0 0 0 0 3 0 2 0 1 0 0 2 0 0 0 0 0 0 0 0 4 0 13 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Bacteria;Chlamydiae;Chlamydiae;Chlamydiales;Chlamydiaceae;Chlamydia;trachomatis
67 | 85 1 3 1 5 3 0 0 1 3 2 0 0 0 5 6 9 1 1 7 0 12 1 0 2 0 4 2 9 0 40 9 1 2 3 0 2 0 0 0 3 2 2 0 4 1 0 0 2 0 0 12 1 3 0 1 3 1 90 3 2 98 1 5 3 0 1 2 0 0 0 0 0 0 1 0 1 0 1 5 359 1 0 7 1 15 4 7 5 2 5 56 2 0 3 0 0 1 0 0 0 0 4 1 0 1 0 1 8 0 0 2 0 0 0 1 0 0 3 0 4 22 21 0 1 4 1 1 1 0 3 0 5 3 0 0 533 0 0 0 1 0 4 2 0 0 2 4 0 4 0 2 5 5 1 1 0 1 1 0 3 3 0 1 4 6 8 0 0 1 0 0 5 1 3 0 3 1 33 7 0 5 9 5 1 2 2 234 3 0 2 0 7 2 2 3 5 1 2 2 1 0 0 7 4 1 1 5 113 16 1 0 1 0 3 6 0 0 12 2 6 3 0 0 3 3 1 2 6 11 0 1 0 2 1 5 1 0 0 1 5 2 5 2 1 4 0 1 0 0 0 1 4 2 1 3 9 1 3 4 1 2 6 1 0 1 322 2 2 2 9 0 0 2 2 1 11 3 0 3 5 5 0 1 3 0 184 0 0 1 4 2 2 2 1 5 5 9 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;unclassified;unclassified
68 | 86 7 2 3 2 2 7 5 2 0 5 2 0 1 3 0 0 1 1 6 0 3 1 3 3 5 2 3 8 2 140 6 0 1 3 1 5 0 0 2 1 7 5 0 1 2 2 0 0 0 2 0 2 0 0 0 0 0 1 0 0 14 0 3 6 1 4 0 1 3 1 0 1 1 2 1 3 1 3 2 3 0 2 0 10 2 0 0 1 2 0 0 3 3 0 2 1 7 4 3 0 0 1 2 4 0 12 3 0 0 0 0 3 0 0 0 3 0 5 2 2 6 8 2 8 1 1 2 3 3 0 5 5 5 74 2 2 1 0 1 5 1 6 1 2 1 0 2 0 0 1 2 4 1 0 1 0 0 0 2 1 6 0 6 0 2 0 4 0 7 1 4 1 2 1 4 1 3 2 385 1 0 1 0 2 0 2 1 12 0 6 2 0 0 0 1 0 1 20 2 0 1 4 4 2 0 0 10 1 1 4 0 0 0 2 1 3 0 2 1 12 1 3 4 1 0 0 8 3 0 1 0 0 9 0 3 0 4 3 6 11 2 0 0 120 1 0 3 162 4 0 1 2 1 0 0 3 3 0 8 0 3 1 0 0 1 7 0 4 3 0 0 0 0 1 8 4 5 0 10 1 6 0 0 0 0 1 5 3 4 1 0 1 4 0 4 0 3 Bacteria;Proteobacteria;Epsilonproteobacteria;Campylobacterales;Campylobacteraceae;Campylobacter;ureolyticus
69 | 90 0 5 4 1 0 0 0 0 1 0 0 0 5 0 0 1 0 0 0 0 5 0 0 0 1 0 4 0 2 0 11 0 1 0 6 15 0 2 0 0 0 2 9 0 0 0 0 0 1 0 4 0 1 2 0 0 0 2 6 5 2 1 0 0 1 0 0 0 3 1 0 0 0 1 0 3 1 1 1 1 0 0 1 1 1 1 0 0 1 2 2 0 2 2 0 0 21 0 0 19 1 1 0 0 0 1 1 0 0 9 0 1 2 13 3 8 1 0 1 0 23 1 0 0 0 0 1 2 0 1 0 3 0 7 2 3 0 0 0 3 0 1565 0 0 1 17 0 0 0 2 1 0 1 0 1 0 0 0 0 1 0 8 23 4 1 6 3 2 6 2 0 0 0 0 0 0 5 1 2 2 3 0 3 0 0 0 1 0 0 6 0 3 0 4 4 0 0 142 7 6 0 0 0 1 1 1 2 0 2 0 1 1 0 0 8 0 1 0 3 0 0 0 1 2 0 0 0 0 0 0 2 0 8 1 0 9 0 0 1 22 2 1 0 0 1 1 0 0 0 2 0 1 2 0 19 0 0 2 13 2 0 0 0 0 0 1 10 1 0 0 1 1 0 19 9 14 2 0 18 0 0 1 0 7 1 0 0 0 5 2 0 0 0 0 28 2 1 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;unclassified
70 | 99 12 0 3 1 0 0 1 0 0 0 0 7 1 0 0 10 0 0 0 1 0 0 0 102 0 25 58 1 0 10 3 4 0 2 0 9 2 0 8 0 0 0 4 0 4 0 8 0 0 0 1 0 0 1 2 0 12 0 2 46 5 0 0 0 0 4 0 0 2 0 0 0 1 4 0 2 0 0 0 1 1 5 0 1 0 0 3 0 0 1 12 0 0 0 0 0 26 1 0 8 0 0 1 0 0 0 0 0 0 5 2 0 0 0 0 2 1 0 3 2 6 16 0 0 1 0 1 1 0 1 0 0 2 0 3 2 0 6 4 5 5 6 0 0 0 0 0 0 1 0 1 3 1 1 0 0 2 1 9 0 0 0 12 0 1 1 1 0 7 0 1 0 2 0 1 0 1 0 14 0 5 0 2 0 0 5 1 0 0 0 1 10 0 2 1 2 40 1 0 0 7 0 0 29 92 0 0 4 12 7 0 2 3 0 2 2 7 0 6 0 0 0 3 3 0 0 1 4 7 0 1 0 5 0 0 1 0 0 0 17 1 1 1 3 0 0 0 0 0 0 1 2 5 2 0 1 0 26 8 0 12 6 70 1 0 16 0 0 3 0 8 0 0 1 17 1 1 0 10 0 26 0 1 0 0 7 0 0 2 2 0 6 0 0 3 0 2 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;unclassified
71 | 101 0 1 0 1 7 0 0 0 2 1 1 0 1 2 3 2 0 0 2 3 2 4 0 1 0 2 6 0 1 11 0 37 0 10 0 2 0 1 0 147 2 3 0 1 1 1 2 1 0 1 2 7 0 0 1 3 0 2 2 0 1 3 4 5 0 1 0 1 0 2 9 1 3 0 8 5 1 0 0 3 0 1 4 0 5 0 2 0 0 3 0 2 0 1 0 9 2 0 8 18 2 3 0 16 0 0 0 5 1 2 3 0 7 1 6 1 0 1 5 0 1 1 0 1 2 0 0 1 2 0 0 2 0 493 0 13 0 2 2 3 0 0 2 0 2 1 1 2 7 1 1 0 0 0 0 1 4 0 2 0 3 0 1 0 0 2 4 6 2 2 1 1 1 0 1 4 2 0 22 0 1 0 0 14 3 0 0 1 1 2 1 0 0 90 0 2 1 2 1 0 1 2 3 2 0 0 1 1 1 2 0 6 4 1 0 1 1 2 0 2 2 4 0 0 0 2 0 1 0 0 2 4 1 8 1 2 5 0 4 0 0 1 1 2 0 9 5 1 2 5 6 1 0 2 2 0 0 2 22 0 7 1 0 1 1 3 0 0 1 2 1 1 0 1 38 2 1 0 1 1 7 1 1 0 18 2 0 0 0 1 0 1 0 0 0 1 0 Bacteria;Firmicutes;Clostridia;Clostridiales;Clostridiales_IncertaeSedisXI;Anaerococcus;hydrogenalis
72 | 103 4 0 5 8 1 4 1 0 1 0 5 14 0 5 3 10 4 0 11 0 3 0 0 3 1 4 2 1 0 313 1 1 1 6 0 1 1 1 3 0 2 3 0 0 3 1 0 1 0 0 1 15 0 0 0 0 7 9 5 0 5 3 0 13 0 2 0 8 1 1 7 0 0 2 1 1 1 2 0 2 0 1 1 8 0 0 1 0 0 6 0 2 1 2 7 0 3 4 4 5 0 12 0 2 0 2 3 1 0 1 0 0 0 0 0 2 0 9 5 6 4 0 0 6 1 0 1 6 0 5 0 2 14 1 5 2 0 1 1 2 2 1 16 1 0 0 12 1 0 0 2 4 2 0 0 25 8 2 0 2 9 0 3 1 2 2 9 1 2 0 8 0 2 0 5 1 2 1 10 4 0 2 0 0 10 0 3 0 2 1 0 1 0 2 2 5 0 4 1 0 3 0 4 3 2 4 0 6 3 2 1 0 4 2 2 11 0 0 0 0 6 0 6 0 1 3 5 13 4 1 5 1 7 3 1 0 2 3 0 3 0 5 6 1 0 1 1 37 2 1 0 0 1 0 0 0 8 0 6 13 6 4 4 0 11 2 0 1 8 0 5 3 0 0 3 0 0 0 6 0 0 0 0 0 1 2 1 0 0 3 0 3 11 0 4 0 1 Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Actinomycetaceae;Actinomyces;turicensis
73 | 136 1 0 1 0 4 1 2 1 0 0 0 0 0 0 3 0 2 0 0 0 0 1 0 1 0 2 7 1 0 23 0 2 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 1 0 3 1 0 2 0 53 0 0 1 0 0 0 0 4 0 2 0 2 5 1 0 0 0 0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 8 0 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 3 0 2 0 0 0 1 0 0 3 0 0 0 0 1 789 1 0 1 0 2 0 0 0 0 0 1 0 0 2 0 0 0 0 1 0 0 1 2 0 0 1 0 1 0 1 0 0 0 2 1 1 0 0 0 1 0 1 0 1 12 0 0 1 0 0 0 0 1 0 1 0 1 0 0 123 0 0 0 26 0 0 3 0 1 0 0 0 1 0 0 1 0 3 4 0 1 0 0 0 0 1 0 2 1 0 0 1 1 0 0 0 1 4 0 3 0 0 6 0 0 0 0 1 0 0 0 3 0 0 0 3 3 1 0 0 0 0 0 0 0 0 2 0 0 7 0 0 0 0 0 1 1 0 0 0 0 2 0 0 0 0 3 0 1 0 1 0 0 0 0 0 0 0 0 2 17 0 1 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;bennonis
74 | 146 1 0 1 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 4 1 0 1 218 0 0 3 0 0 0 1 0 3 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2 0 2 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 5 1 0 0 0 0 0 0 3 0 0 2 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 0 0 0 0 0 1 0 0 0 4 0 0 0 0 0 0 0 50 0 1 0 0 0 0 0 0 1 0 0 0 0 0 4 2 0 0 56 0 1 1 0 2 0 0 0 0 0 4 1 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 1 0 0 0 0 0 0 0 0 1 0 2 0 0 1 0 0 0 1 0 0 0 0 0 0 0 2 1 2 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 3 0 0 0 0 0 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Porphyromonadaceae;Porphyromonas;somerae
75 | 292 1 0 1 3 2 0 0 0 0 0 0 1 0 0 1 6 1 1 3 0 1 2 0 13 1 150 14 0 0 2 1 0 0 4 0 0 0 2 3 0 1 0 5 0 0 0 4 1 0 0 2 0 1 1 0 4 1 0 1 5 1 0 0 1 0 0 0 1 3 0 1 1 0 2 0 0 0 0 0 0 0 6 0 1 6 0 0 2 0 2 2 1 1 0 1 0 1 2 0 0 0 1 0 0 2 0 1 0 0 0 0 0 1 0 0 0 0 0 1 3 5 4 0 0 2 0 0 0 0 0 0 2 2 0 1 0 0 2 2 0 0 1 0 0 0 0 1 0 3 5 1 3 0 1 1 0 2 1 1 0 0 1 2 1 2 7 0 0 0 1 0 0 2 2 2 1 0 0 3 0 2 0 0 0 0 4 49 0 3 0 0 59 0 6 1 3 5 0 0 0 0 0 1 2 8 0 0 6 2 4 0 0 5 0 2 1 7 0 3 0 0 0 0 1 0 3 1 5 2 0 1 0 0 0 1 1 3 0 0 0 0 0 0 2 0 1 0 2 0 0 1 0 0 2 2 0 2 455 7 1 6 5 5 1 1 6 0 0 0 1 2 0 6 1 0 0 0 0 0 0 10 0 1 0 1 1 0 0 0 0 0 2 1 0 1 0 1 Bacteria;Bacteroidetes;Bacteroidia;Bacteroidales;Prevotellaceae;Prevotella;unclassified
76 | 300 3 0 110 3 2 0 5 11 0 1 0 1 4 0 0 1 0 1 1 0 1 0 1 3 0 3 0 51 0 0 8 1 0 0 3 0 0 1 1 1 4 1 1 1 0 0 1 0 0 0 0 0 1 2 1 1 1 0 2 4 0 3 0 0 3 0 0 0 1 0 1 3 5 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 9 2 3 0 24 1 3 0 6 1 0 1 0 2 1 0 5 9 0 1 0 3 1 3 2 5 0 2 0 0 9 3 1 0 1 5 0 0 1 1 9 0 3 0 8 0 0 1 1 2 2 0 117 5 6 0 0 2 0 7 13 0 1 0 0 0 2 3 6 0 14 0 0 0 13 1 4 5 0 11 0 0 0 0 1 0 0 0 0 9 3 0 1 0 4 0 0 1 1 0 4 0 0 1 2 1 1 1 2 1 5 1 1 1 0 2 0 0 4 0 3 5 0 1 1 2 2 9 0 6 2 3 0 1 0 0 1 0 8 3 0 650 0 3 1 0 1 4 0 3 5 3 0 0 2 4 0 0 2 1 0 0 2 0 6 6 0 0 5 1 1 3 1 4 2 0 0 0 1 0 0 0 2 1 5 1 5 0 0 0 0 14 1 0 1 0 0 1 4 1 2 2 0 2 2 0 7 0 1 Bacteria;Actinobacteria;Actinobacteria;Bifidobacteriales;Bifidobacteriaceae;Gardnerella;vaginalis;unclassified
77 | 372 0 0 0 0 1 0 13 0 0 15 0 1 0 2 0 0 0 0 1 0 8 0 0 1 0 0 0 1170 0 0 0 0 0 0 0 0 0 0 0 1 1 10 0 0 0 0 0 0 0 0 2 0 0 0 11 1 0 0 17 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 18 0 0 0 3 0 1 0 0 14 0 0 0 6 14 0 20 0 0 0 4 0 0 0 0 0 202 0 0 0 0 0 1 0 0 0 0 7 0 0 0 0 10 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 4 0 0 2 0 0 1 0 12 8 0 0 0 0 0 0 0 0 12 0 0 3 0 0 0 0 0 0 0 2 0 0 0 0 2 1 0 0 1 0 1 0 6 0 0 0 12 0 0 0 0 1 1 0 1 0 1 2 0 0 1 0 0 0 5 3 1 0 0 0 0 1 0 0 0 2 111 1 2 0 0 0 0 17 0 13 0 0 0 5 0 0 1 1 1 0 1 0 0 0 6 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 9 0 1 0 0 1 0 0 0 0 0 0 9 0 Bacteria;Firmicutes;Bacilli;Lactobacillales;Lactobacillaceae;Lactobacillus;unclassified
78 | 384 2 2 116 0 3 0 2 5 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 1 0 8 2 41 0 1 5 1 0 2 1 0 0 1 0 0 5 4 0 0 0 0 1 0 0 0 0 0 1 2 2 0 0 0 3 3 0 8 0 2 3 0 0 0 3 0 0 2 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 15 1 0 0 4 0 1 0 0 1 0 0 2 8 0 0 0 5 2 4 1 1 0 1 0 1 8 2 0 6 0 10 1 0 0 3 8 0 4 1 19 0 0 1 0 2 1 0 67 12 4 0 0 3 0 0 5 1 0 1 2 0 1 4 3 0 26 0 0 0 1 0 0 2 0 9 0 0 0 0 0 2 1 0 0 7 0 0 0 0 3 0 0 1 1 0 8 0 0 0 2 2 1 1 0 2 2 0 1 0 0 5 3 1 6 0 1 0 0 1 0 0 1 9 0 5 0 1 0 1 0 0 1 0 3 4 0 572 0 3 3 0 0 9 0 1 2 0 0 0 0 3 0 0 1 1 0 0 0 0 4 12 0 1 4 0 2 2 0 0 0 2 0 0 0 0 2 0 1 0 4 0 2 0 0 0 0 6 1 0 0 0 0 2 1 0 2 0 0 1 3 1 1 0 0 Bacteria;Actinobacteria;Actinobacteria;Bifidobacteriales;Bifidobacteriaceae;Gardnerella;vaginalis;unclassified
79 |
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/inst/shiny-app/example_metadata.txt:
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1 | #SampleID Ltag-Rtag person_id time study probio age b_contra b_horm b_reg b_recur b_s_odor b_s_dyspar b_s_dysur b_s_burn b_s_itch a_dis a_whiff a_ph a_clue n_status cand_col c_albic c_trop c_other d_in d_cris d_jens d_other ad_gas ad_cris ad_jens ad_john ad_other CD4_count study_probio_time
2 | 2bcont CATGCG-GCAGT 2 0 b_cont NA 35 y n n ND n n n n n n n 0 ND n n n n n y n y n n n y n n NA bcont_NA_0
3 | 3bcont CATGCG-TAGCT 3 0 b_cont NA 44 n n y ND y n n n y n n 0 ND n n n n n n n y n n y n n L_aci NA bcont_NA_0
4 | 4bcont CATGCG-GACTGT 4 0 b_cont NA 33 y n y ND n n n n n n n 0 ND n n n n n n n y n n y y n n NA bcont_NA_0
5 | 5bcont CATGCG-CGTCGA 5 0 b_cont NA 33 y n n ND n n n n y n n 0 ND n p n y n n n y n n y n n n NA bcont_NA_0
6 | 6bcont CATGCG-GTCGC 6 0 b_cont NA 21 y y n ND n n n n n n n 0 ND n p y n n y n n n n n n y n NA bcont_NA_0
7 | 7bcont CATGCG-ACGTA 7 0 b_cont NA 36 y y y ND n y n n n n n 0 ND n p y n n n y n n n y n n n NA bcont_NA_0
8 | 8bcont CATGCG-CACTAC 8 0 b_cont NA 18 y y y ND n n n n n n n 0 ND n n n n n y n y n n n y n n NA bcont_NA_0
9 | 9bcont CATGCG-TGAC 9 0 b_cont NA 29 y n n ND n n n n y n n 0 ND n n n n n y n n n n n n y n NA bcont_NA_0
10 | 10bcont CATGCG-AGTA 10 0 b_cont NA 38 y y n ND n n n n n n n 0 ND n p y n n y n n n n y y n L_vagi NA bcont_NA_0
11 | 11bcont CATGCG-ATGA 11 0 b_cont NA 43 n n y ND n n n n n n n 0 ND n p n y C_no_albi y y n n n y n n n NA bcont_NA_0
12 | 12bcont CATGCG-TGCA 12 0 b_cont NA 20 y y y ND n n n n n n n 0 ND n n n n n n y n L_john y n n n n NA bcont_NA_0
13 | 13bcont CATGCG-ACT 13 0 b_cont NA 33 y y n ND n n n n n n n 0 ND n p y n n n y n n n y n n n NA bcont_NA_0
14 | 14bcont CATGCG-TCG 14 0 b_cont NA 33 n n y ND n n n n n n n 0 ND n n n n n y n n n n n n n L_ruminus NA bcont_NA_0
15 | 15bcont CATGCG-GTA 15 0 b_cont NA 26 y y n ND n y n n n n n 0 ND n n n n n n y n n n y n n n NA bcont_NA_0
16 | 16bcont CATGCG-CTA 16 0 b_cont NA 32 n n n ND n n n n n n n 0 ND n n n n n n n n L_john y n n n n NA bcont_NA_0
17 | 17bcont CATGCG-GAGG 17 0 b_cont NA 21 y y y ND n y n n n n n 0 ND n p y n n y y n n n n n n L_vagi-L_salivarius NA bcont_NA_0
18 | 18bcont CATGCG-GAAG 18 0 b_cont NA 39 n n y ND n n n n n n n 0 ND n n n n n y y n n n n n y n NA bcont_NA_0
19 | 19bcont CATGCG-ATT 19 0 b_cont NA 25 y y y ND n n n n n n n 0 ND n n n n n y n n n n n n n L_agilis NA bcont_NA_0
20 | 20bcont CATGCG-AGG 20 0 b_cont NA 19 y n y ND n n n n n n n 0 ND n n n n n y n n n y n n n n NA bcont_NA_0
21 | 21bcont CATGCG-AGCC 21 0 b_cont NA 45 n n n ND y n n n n n n 0 ND n n n n n y n n n y n n n L_coleohominis NA bcont_NA_0
22 | 22bcont CATGCG-GACC 22 0 b_cont NA 21 y y y ND n n n n y n n 0 ND n n n n n y n n n n y n n n NA bcont_NA_0
23 | 23bcont CATGCG-CCTT 23 0 b_cont NA 18 y y y ND n n n n n n n 0 ND n n n n n n y n n n y n n n NA bcont_NA_0
24 | 24bcont CATGCG-CGTTG 24 0 b_cont NA 23 y y y ND n n n n n n n 0 ND n n n n n n y n n n y n n n NA bcont_NA_0
25 | 25bcont GCAGT-CATGCG 25 0 b_cont NA 30 y y y ND n y n n n n n 0 ND n n n n n y n n n n y n n n NA bcont_NA_0
26 | 26bcont GCAGT-GCAGT 26 0 b_cont NA 21 n n y ND n n n n n n n 0 ND n n n n n n y n n n y n n n NA bcont_NA_0
27 | 27bcont GCAGT-TAGCT 27 0 b_cont NA 47 n n y ND n n n n n n n 0 ND n n n n n n n n L_gas y n n n n NA bcont_NA_0
28 | 28bcont GCAGT-GACTGT 28 0 b_cont NA 20 y y y ND n n n n n n n 0 ND n p y n n y n n L_gas n n n n L_vagi NA bcont_NA_0
29 | 29bcont GCAGT-CGTCGA 29 0 b_cont NA 18 y y n ND n n n n n n n 0 ND n n n n n n y n n n y n n n NA bcont_NA_0
30 | 30bcont GCAGT-GTCGC 30 0 b_cont NA 39 n n y ND n n n n n n n 0 ND n n n n n n y n n n n n n n NA bcont_NA_0
31 | 31bcont GCAGT-ACGTA 31 0 b_cont NA 34 y y y ND n n n n n n n 0 ND n p y n n n y y n n n n y L_vagi NA bcont_NA_0
32 | 32bcont GCAGT-CACTAC 32 0 b_cont NA 40 n n y ND n n n n n n n 0 ND n p n y C_no_albi y n n n n n n n L_fermentum NA bcont_NA_0
33 | 33bcont GCAGT-TGAC 33 0 b_cont NA 23 y y y ND n n n n n n n 0 ND n p y n n y n n n y n n n L_vagi NA bcont_NA_0
34 | 34bcont GCAGT-AGTA 34 0 b_cont NA 30 n n y ND n n n n n n n 0 ND n n n n n y n n n n y n y n NA bcont_NA_0
35 | 35bcont GCAGT-ATGA 35 0 b_cont NA 36 n n y ND n n n n n n n 0 ND n n n n n n n n L_gas-L_reut n n n n n NA bcont_NA_0
36 | 36bcont GCAGT-TGCA 36 0 b_cont NA 34 n n y ND n n n n n n n 0 ND n p y n n y y n n n y n n n NA bcont_NA_0
37 | 37bcont GCAGT-ACT 37 0 b_cont NA 45 n n y ND n n n n n n n 0 ND n n n n n y y n n n y n y n NA bcont_NA_0
38 | 38bcont GCAGT-TCG 38 0 b_cont NA 47 y n y ND n n n n n n n 0 ND n n n n n n n n n n n n n L_aci NA bcont_NA_0
39 | 39bcont GCAGT-GTA 39 0 b_cont NA 31 y n y ND y n n n n n n 0 ND n p y n n n n n L_aci n n y n L_agilis NA bcont_NA_0
40 | 40bcont GCAGT-CTA 40 0 b_cont NA 18 y y y ND n n n n n n n 0 ND n n n n n y y n n n n n n n NA bcont_NA_0
41 | 41bcont GCAGT-GAGG 41 0 b_cont NA 44 n n n ND n n n n n n n 0 ND n n n n n y n n L_aci n y n n n NA bcont_NA_0
42 | 42bcont GCAGT-GAAG 42 0 b_cont NA 33 n n n ND n n n n n n n 0 ND n n n n n y n n n n y n n n NA bcont_NA_0
43 | 43bcont GCAGT-ATT 43 0 b_cont NA 23 y y y ND n n n n n n n 0 ND n n n n n n n n L_aci n y n n n NA bcont_NA_0
44 | 44bcont GCAGT-AGG 44 0 b_cont NA 35 y y y ND n n n n n n n 0 ND n n n n n y n n n n n y n n NA bcont_NA_0
45 | 45bcont GCAGT-AGCC 45 0 b_cont NA 28 y y y ND n n n n n n n 0 ND n n n n n y n n n n n n n n NA bcont_NA_0
46 | 46bcont GCAGT-GACC 46 0 b_cont NA 21 y y y ND n n n n n n n 0 ND n n n n n n y n n n y n n n NA bcont_NA_0
47 | 47bcont GCAGT-CCTT 47 0 b_cont NA 41 y y y ND n n n n n n n 0 ND n n n n n y n n n n y n y n NA bcont_NA_0
48 | 48bcont GCAGT-CGTTG 48 0 b_cont NA 38 y n y ND n n n n n n n 0 ND n p n y C_no_albi y n n n n n y n n NA bcont_NA_0
49 | 49bcont TAGCT-CATGCG 49 0 b_cont NA 26 y n y ND n y n n n n n 0 ND n n n n n y n n n n n n y L_agilis NA bcont_NA_0
50 | 50bcont TAGCT-GCAGT 50 0 b_cont NA 38 n n y ND n n n n n n n 0 ND n n n n n n n n L_reut n n n n L_vagi NA bcont_NA_0
51 | 51bcont TAGCT-TAGCT 51 0 b_cont NA 33 y y y ND n n n n n n n 0 ND n n n n n n n y n n n n y n NA bcont_NA_0
52 | 52bcont TAGCT-GACTGT 52 0 b_cont NA 34 y y n ND n n y n n n n 0 ND n n n n n n y n n n n n n n NA bcont_NA_0
53 | 53bcont TAGCT-CGTCGA 53 0 b_cont NA 28 y y n ND n n n n n n n 0 ND n p n y n y n n n n n n y n NA bcont_NA_0
54 | 54bcont TAGCT-GTCGC 54 0 b_cont NA 37 n n y ND n n n n n n n 0 ND n n n n n y n n n n n n n n NA bcont_NA_0
55 | 55bcont TAGCT-ACGTA 55 0 b_cont NA 26 n n n ND n n n n n n n 0 ND n n n n n y y n n n y n n L_aci NA bcont_NA_0
56 | 56bcont TAGCT-CACTAC 56 0 b_cont NA 43 n n y ND n n n n n n n 0 ND n n n n n y n n n n y n n n NA bcont_NA_0
57 | 57bcont TAGCT-TGAC 57 0 b_cont NA 32 y y y ND n y n n n n n 0 ND n n n n n y n n n n n n y L_agilis NA bcont_NA_0
58 | 58bcont TAGCT-AGTA 58 0 b_cont NA 34 n n y ND n y n y n n n 0 ND n n n n n y n n n n n n n n NA bcont_NA_0
59 | 59bcont TAGCT-ATGA 59 0 b_cont NA 33 y n y ND n n n n n n n 0 ND n p y n n y n n n n y n n n NA bcont_NA_0
60 | 60bcont TAGCT-TGCA 60 0 b_cont NA 27 y y y ND n n n n n n n 0 ND n n n n n n y n n n y n n L_aci NA bcont_NA_0
61 | 61bcont TAGCT-ACT 61 0 b_cont NA 25 y y y ND n n n n y n n 0 ND n p n y C_no_albi y n n n y n n n n NA bcont_NA_0
62 | 62bcont TAGCT-TCG 62 0 b_cont NA 32 n n y ND n y n n n n n 0 ND n n n n n y n n n n n n n n NA bcont_NA_0
63 | 63bcont TAGCT-GTA 63 0 b_cont NA 27 y n y ND n n n n n n n 0 ND n n n n n n n y n n n y n n NA bcont_NA_0
64 | 64bcont TAGCT-CTA 64 0 b_cont NA 45 n n y ND n n n n n n n 0 ND n n n n n y n n L_aci n y n n n NA bcont_NA_0
65 | 65bvvc TAGCT-GAGG 65 0 b_vvc n 26 y y y n n n n n y y n 0 ND n/i p y n n y n n n y n n n n NA bvvc_n_0
66 | 66bvvc TAGCT-GAAG 65 1 b_vvc n 26 y y y n n ND ND n n y n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
67 | 67bvvc TAGCT-ATT 66 0 b_vvc n 36 y n y n y n n n y y n 0 ND n/i p y n n n y n n y y y n n NA bvvc_n_0
68 | 68bvvc TAGCT-AGG 66 1 b_vvc n 36 y n y n y ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
69 | 69bvvc TAGCT-AGCC 67 0 b_vvc y 21 n n n n n n n y y y n 0 ND n/i p y n n n y n n y y n n n NA bvvc_y_0
70 | 70bvvc TAGCT-GACC 67 1 b_vvc y 21 n n n n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
71 | 71bvvc TAGCT-CCTT 68 0 b_vvc n 41 y n y n n y n y y y n 0 ND n/i p y n n n y n n n y n n n NA bvvc_n_0
72 | 72bvvc TAGCT-CGTTG 68 1 b_vvc n 41 y n y n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
73 | 73bvvc GACTGT-CATGCG 69 0 b_vvc y 34 y y n n n y n y y y n 0 ND n/i p y n n n y n n n y n n n NA bvvc_y_0
74 | 74bvvc GACTGT-GCAGT 69 1 b_vvc y 34 y y n n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
75 | 75bvvc GACTGT-TAGCT 70 0 b_vvc y 46 n n y y n n n n y y n 0 ND n/i p n n n y n n n n n n n n NA bvvc_y_0
76 | 76bvvc GACTGT-GACTGT 70 1 b_vvc y 46 n n y y n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
77 | 77bvvc GACTGT-CGTCGA 71 0 b_vvc n 31 y y n n y n n y y y n 0 ND n/i p y n n n y n n n y n n n NA bvvc_n_0
78 | 78bvvc GACTGT-GTCGC 71 1 b_vvc n 31 y y n n n ND ND n n n n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
79 | 79bvvc GACTGT-ACGTA 72 0 b_vvc y 19 y y n n n n n n n y n 0 ND n/i p y n n y n n n y n n n L_fermentum NA bvvc_y_0
80 | 80bvvc GACTGT-CACTAC 72 1 b_vvc y 19 y y n n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
81 | 81bvvc GACTGT-TGAC 73 0 b_vvc y 29 y n y n n n n n n y n 0 ND n/i p y n n y n n n n n y n n NA bvvc_y_0
82 | 82bvvc GACTGT-AGTA 73 1 b_vvc y 29 y n y n n ND ND n n n n 1 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
83 | 85bvvc GACTGT-ACT 75 0 b_vvc n 17 y y y n n n n n y y n 0 ND n/i p n n C_glabrata n y n n n y n y n NA bvvc_n_0
84 | 86bvvc GACTGT-TCG 75 1 b_vvc n 17 y y y n n ND ND y y y n 0 ND ND p y n C_glabrata NA NA NA NA NA NA NA NA NA NA bvvc_n_1
85 | 89bvvc GACTGT-GAGG 77 0 b_vvc y 32 y y y n n n n y y y n 0 ND n/i p y n n n n n L_reut y n n n n NA bvvc_y_0
86 | 90bvvc GACTGT-GAAG 77 1 b_vvc y 32 y y y n n ND ND n n n y 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
87 | 93bvvc GACTGT-AGCC 79 0 b_vvc n 25 y y y n n y y y y y n 0 ND n/i p y n n n y n n n y y n n NA bvvc_n_0
88 | 94bvvc GACTGT-GACC 79 1 b_vvc n 25 y y y n n ND ND n n n n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
89 | 95bvvc GACTGT-CCTT 80 0 b_vvc n 38 y n y n n y n n y y n 0 ND n/i p y n n n y n n n n n n L_rhamnosus NA bvvc_n_0
90 | 96bvvc GACTGT-CGTTG 80 1 b_vvc n 38 y n y n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
91 | 101bvvc CGTCGA-CGTCGA 83 0 b_vvc y 38 y y y y n y y y y y n 0 ND n/i p y n n n y n n n y n n n NA bvvc_y_0
92 | 102bvvc CGTCGA-GTCGC 83 1 b_vvc y 38 y y y y n ND ND n n n n 1 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
93 | 103bvvc CGTCGA-ACGTA 84 0 b_vvc n 21 n n y y n y y y y y n 0 ND n/i p y n n n n n n y n n n n NA bvvc_n_0
94 | 104bvvc CGTCGA-CACTAC 84 1 b_vvc n 21 n n y y n ND ND y y y n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
95 | 105bvvc CGTCGA-TGAC 85 0 b_vvc n 34 y n y n n n n y y y n 0 ND n/i p n y n y n n L_reut y n n n n NA bvvc_n_0
96 | 106bvvc CGTCGA-AGTA 85 1 b_vvc n 34 y n y n n ND ND y n y y 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
97 | 107bvvc CGTCGA-ATGA 86 0 b_vvc y 33 y n n n n n n y y y n 0 ND n/i p y n n n n n n y n n n n NA bvvc_y_0
98 | 108bvvc CGTCGA-TGCA 86 1 b_vvc y 33 y n n n n ND ND n n y n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
99 | 111bvvc CGTCGA-GTA 88 0 b_vvc n 28 n n y y n n n n y y n 0 ND n/i p y n n y n n n n n n n L_vagi NA bvvc_n_0
100 | 112bvvc CGTCGA-CTA 88 1 b_vvc n 28 n n y y n ND ND n n y n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
101 | 113bvvc CGTCGA-GAGG 89 0 b_vvc y 29 y y y y n n n y y y n 0 ND n/i p y n n n y n n n y n n n NA bvvc_y_0
102 | 114bvvc CGTCGA-GAAG 89 1 b_vvc y 29 y y y y n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
103 | 115bvvc CGTCGA-ATT 90 0 b_vvc n 21 y y y n n n n n y y n 0 ND n/i p y n n y n n n n y n n n NA bvvc_n_0
104 | 116bvvc CGTCGA-AGG 90 1 b_vvc n 21 y y y n n ND ND n y y n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
105 | 117bvvc CGTCGA-AGCC 91 0 b_vvc n 28 y y n n n y n y y y n 0 ND n/i p y n n y n n n n n n y n NA bvvc_n_0
106 | 118bvvc CGTCGA-GACC 91 1 b_vvc n 28 y y n n n ND ND n y n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
107 | 119bvvc CGTCGA-CCTT 92 0 b_vvc n 35 y y y n n n n n n y n 0 ND n/i p y n n y y n n y n n n n NA bvvc_n_0
108 | 120bvvc CGTCGA-CGTTG 92 1 b_vvc n 35 y y y n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
109 | 121bvvc GTCGC-CATGCG 93 0 b_vvc n 19 n n y n n n n y n y n 0 ND n/i p y n n y y n n n y n n n NA bvvc_n_0
110 | 122bvvc GTCGC-GCAGT 93 1 b_vvc n 19 n n y n n ND ND y n y n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
111 | 123bvvc GTCGC-TAGCT 94 0 b_vvc n 17 y y y n n n n y y y n 0 ND n/i p y n n n n n L_plantarum-L_sakei n y n n L_reuteri NA bvvc_n_0
112 | 124bvvc GTCGC-GACTGT 94 1 b_vvc n 17 y y y n n ND ND n n y n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
113 | 125bvvc GTCGC-CGTCGA 95 0 b_vvc n 21 y y y y n y n y y y n 0 ND n/i p y n n y y n n n y y n n NA bvvc_n_0
114 | 126bvvc GTCGC-GTCGC 95 1 b_vvc n 21 y y y y n ND ND y y y n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
115 | 129bvvc GTCGC-TGAC 97 0 b_vvc y 32 y y y y n n n y y y n 0 ND n/i p y n n y n n L_plantarum n n y n n NA bvvc_y_0
116 | 130bvvc GTCGC-AGTA 97 1 b_vvc y 32 y y y y n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
117 | 131bvvc GTCGC-ATGA 98 0 b_vvc y 28 y y n n n n n n y y n 0 ND n/i p y n n y n n n n n n n n NA bvvc_y_0
118 | 132bvvc GTCGC-TGCA 98 1 b_vvc y 28 y y n n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
119 | 135bvvc GTCGC-GTA 100 0 b_vvc n 23 n n n n n n n n y y n 0 ND n/i p y n n n n n L.reut y n n n L_vagi NA bvvc_n_0
120 | 136bvvc GTCGC-CTA 100 1 b_vvc n 23 n n n n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
121 | 137bvvc GTCGC-GAGG 101 0 b_vvc y 25 y y n n n y n y y y n 0 ND n/i p y n n n y n n n y n n n NA bvvc_y_0
122 | 138bvvc GTCGC-GAAG 101 1 b_vvc y 25 y y n n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
123 | 139bvvc GTCGC-ATT 102 0 b_vvc y 26 n n y n n n n y y y n 0 ND n/i p y n n n y n n n n n y n NA bvvc_y_0
124 | 140bvvc GTCGC-AGG 102 1 b_vvc y 26 n n y n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
125 | 141bvvc GTCGC-AGCC 103 0 b_vvc y 23 n n n n n y n n n y n 0 ND n/i p y n n y n n n n n y n n NA bvvc_y_0
126 | 142bvvc GTCGC-GACC 103 1 b_vvc y 23 n n n n n ND ND n n y n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
127 | 143bvvc GTCGC-CCTT 104 0 b_vvc y 17 n n y n n n n y y y n 0 ND n/i p y n n n y n n n y y n n NA bvvc_y_0
128 | 144bvvc GTCGC-CGTTG 104 1 b_vvc y 17 n n y n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
129 | 145bvvc ACGTA-CATGCG 105 0 b_vvc y 16 y y y y n y n y y y n 0 ND n/i p y n n y n n n n y n n n NA bvvc_y_0
130 | 146bvvc ACGTA-GCAGT 105 1 b_vvc y 16 y y y y n ND ND y n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
131 | 149bvvc ACGTA-CGTCGA 107 0 b_vvc y 39 y y y n n n n n n y n 0 ND n/i p y n n n y n n n y n n n NA bvvc_y_0
132 | 150bvvc ACGTA-GTCGC 107 1 b_vvc y 39 y y y n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
133 | 153bvvc ACGTA-TGAC 109 0 b_vvc n 33 y y y n n y y y y y n 0 ND n/i p y n n n y n L_fermentum n y n n n NA bvvc_n_0
134 | 154bvvc ACGTA-AGTA 109 1 b_vvc n 33 y y y n n ND ND n y y n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
135 | 155bvvc ACGTA-ATGA 110 0 b_vvc n 19 n n y y n n n n n y n 0 ND n/i p y n n n n n L_reut n n y n L_vagi NA bvvc_n_0
136 | 156bvvc ACGTA-TGCA 110 1 b_vvc n 19 n n y y n ND ND n n y n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
137 | 157bvvc ACGTA-ACT 111 0 b_vvc n 29 y y y n y y y y y y n 1 ND n/i p y n n y n n n y n n n n NA bvvc_n_0
138 | 158bvvc ACGTA-TCG 111 1 b_vvc n 29 y y y n n ND ND n n n y 1 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
139 | 159bvvc ACGTA-GTA 112 0 b_vvc y 24 y n y n n n n n y y n 0 ND n/i p y n n y n n n n n n n n NA bvvc_y_0
140 | 160bvvc ACGTA-CTA 112 1 b_vvc y 24 y n y n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
141 | 163bvvc ACGTA-ATT 114 0 b_vvc y 30 n n y y n y n y y y n 0 ND n/i p y n n y n n n n n n n n NA bvvc_y_0
142 | 164bvvc ACGTA-AGG 114 1 b_vvc y 30 n n y y n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
143 | 165bvvc ACGTA-AGCC 115 0 b_vvc y 19 n n n n n n y n y y n 0 ND n/i p y n n n n n L_reut n y n n n NA bvvc_y_0
144 | 166bvvc ACGTA-GACC 115 1 b_vvc y 19 n n n n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
145 | 167bvvc ACGTA-CCTT 116 0 b_vvc n 30 y y y n n n n y n y n 0 ND n/i p y n n y n n n n n y n n NA bvvc_n_0
146 | 168bvvc ACGTA-CGTTG 116 1 b_vvc n 30 y y y n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
147 | 169bvvc CACTAC-CATGCG 117 0 b_vvc y 23 y y y y n y n y y y n 0 ND n/i p y n n n y n n n n y n L_ferrmentum NA bvvc_y_0
148 | 170bvvc CACTAC-GCAGT 117 1 b_vvc y 23 y y y y n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
149 | 171bvvc CACTAC-TAGCT 118 0 b_vvc y 39 y n y y n n n n y y n 0 ND n/i p y n n y n n n n n y n n NA bvvc_y_0
150 | 172bvvc CACTAC-GACTGT 118 1 b_vvc y 39 y n y y n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
151 | 173bvvc CACTAC-CGTCGA 119 0 b_vvc y 30 n n y y n y n y y y n 0 ND n/i p y n n n n n L_johnsonii y n n n n NA bvvc_y_0
152 | 174bvvc CACTAC-GTCGC 119 1 b_vvc y 30 n n y y n ND ND n n n n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
153 | 175bvvc CACTAC-ACGTA 120 0 b_vvc n 16 y y y n y n n n n y n 0 ND n/i p n n C_parapsilosis n y n n n y n n n NA bvvc_n_0
154 | 176bvvc CACTAC-CACTAC 120 1 b_vvc n 16 y y y n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
155 | 181bvvc CACTAC-ACT 123 0 b_vvc n 42 y n y n y y y y n y n 0 ND n/i p y n n n y n n n y y n n NA bvvc_n_0
156 | 182bvvc CACTAC-TCG 123 1 b_vvc n 42 y n y n y ND ND y n y n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
157 | 183bvvc CACTAC-GTA 124 0 b_vvc n 25 y y y n n n n y y y n 0 ND n/i p y n n y y n n n y y n n NA bvvc_n_0
158 | 184bvvc CACTAC-CTA 124 1 b_vvc n 25 y y y n n ND ND y n y n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
159 | 185bvvc CACTAC-GAGG 125 0 b_vvc y 34 n n y y n n n y n y n 0 ND n/i p y n n y n n n n n n n n NA bvvc_y_0
160 | 186bvvc CACTAC-GAAG 125 1 b_vvc y 34 n n y y n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
161 | 187bvvc CACTAC-ATT 126 0 b_vvc y 27 y y n y n n y y y y n 0 ND n/i p y n n y n n n n n n y n NA bvvc_y_0
162 | 188bvvc CACTAC-AGG 126 1 b_vvc y 27 y y n y n ND ND n y n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
163 | 189bvvc CACTAC-AGCC 127 0 b_vvc y 30 y n n n y y n y y y n 0 ND n/i p y n n y n n n y n y y n NA bvvc_y_0
164 | 190bvvc CACTAC-GACC 127 1 b_vvc y 30 y n n n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
165 | 191bvvc CACTAC-CCTT 128 0 b_vvc y 45 n n y y n n n n n y n 0 ND n/i p n n C_krusei y n n n y n n n n NA bvvc_y_0
166 | 192bvvc CACTAC-CGTTG 128 1 b_vvc y 45 n n y y n ND ND n n y n 0 ND ND p y n C_krusei NA NA NA NA NA NA NA NA NA NA bvvc_y_1
167 | 193bvvc TGAC-CATGCG 129 0 b_vvc n 18 n n n y y n y n y y y 1 ND n/i p n n C_parapsilosis y n n n n n n n n NA bvvc_n_0
168 | 194bvvc TGAC-GCAGT 129 1 b_vvc n 18 n n n y n ND ND y n y y 0 ND ND p n n C_parapsilosis NA NA NA NA NA NA NA NA NA NA bvvc_n_1
169 | 195bvvc TGAC-TAGCT 130 0 b_vvc y 35 n n y n n y n y n y y 0 ND n/i p y n n y y n n n n n n n NA bvvc_y_0
170 | 196bvvc TGAC-GACTGT 130 1 b_vvc y 35 n n y n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
171 | 197bvvc TGAC-CGTCGA 131 0 b_vvc y 22 y n y n n y n n y y n 0 ND n/i p y n n y y n n n n n n L_aci-L_coleohominis NA bvvc_y_0
172 | 198bvvc TGAC-GTCGC 131 1 b_vvc y 22 y n y n n ND ND n n n n 0 ND ND n n n n NA NA NA NA NA NA NA NA NA NA bvvc_y_1
173 | 199bvvc TGAC-ACGTA 132 0 b_vvc n 16 n n n n n n n y y y n 0 ND n/i p y n n n y n n n y n n n NA bvvc_n_0
174 | 200bvvc TGAC-CACTAC 132 1 b_vvc n 16 n n n n n ND ND n n y n 0 ND ND p y n n NA NA NA NA NA NA NA NA NA NA bvvc_n_1
175 | 201bbv TGAC-TGAC 133 0 b_bv n 27 y n y n y n n n n y y 1 y bv n n n n y n n n n n n n n NA bbv_n_0
176 | 202bbv TGAC-AGTA 133 1 b_bv n 27 y n y n n ND ND n n y y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
177 | 203bbv TGAC-ATGA 134 0 b_bv n 25 y y y n y n n n y y y 1 y bv n n n n y n y n n n n n n NA bbv_n_0
178 | 204bbv TGAC-TGCA 134 1 b_bv n 25 y y y n n ND ND y y y n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
179 | 205bbv TGAC-ACT 135 0 b_bv n 29 n n y n y y n n y y y 1 y bv n n n n n n n n n n n n n NA bbv_n_0
180 | 206bbv TGAC-TCG 135 1 b_bv n 29 n n y n n ND ND n n y y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
181 | 207bbv TGAC-GTA 136 0 b_bv y 42 n n n y y n n n n y y 1 y bv n n n n n n n n n n n n n NA bbv_y_0
182 | 208bbv TGAC-CTA 136 1 b_bv y 42 n n n y n ND ND y y y n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
183 | 209bbv TGAC-GAGG 137 0 b_bv y 19 y y y n y n n n n y y 1 y bv n n n n y n n n n n n n n NA bbv_y_0
184 | 210bbv TGAC-GAAG 137 1 b_bv y 19 y y y n n ND ND n n n y 1 ND i p y n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
185 | 211bbv TGAC-ATT 138 0 b_bv n 36 y n n y y n n n n y y 1 y bv n n y n n n n n y n n n n NA bbv_n_0
186 | 212bbv TGAC-AGG 138 1 b_bv n 36 y n n y y ND ND n n y y 1 ND bv p y y n NA NA NA NA NA NA NA NA NA NA bbv_n_1
187 | 213bbv TGAC-AGCC 139 0 b_bv n 46 y n n n y n n y y y y 1 y bv n n n n n n n n n n n n n NA bbv_n_0
188 | 214bbv TGAC-GACC 139 1 b_bv n 46 y n n n y ND ND n n y y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
189 | 219bbv AGTA-TAGCT 142 0 b_bv n 40 y n y y y n n n n y y 1 y bv n n n n n n n n n n n n n NA bbv_n_0
190 | 220bbv AGTA-GACTGT 142 1 b_bv n 40 y n y y y ND ND n n y n 0 ND i n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
191 | 221bbv AGTA-CGTCGA 143 0 b_bv n 21 y y n y y n y n y y y 1 y bv n y n n y n n n y n n n n NA bbv_n_0
192 | 222bbv AGTA-GTCGC 143 1 b_bv n 21 y y n y n ND ND n n n y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
193 | 223bbv AGTA-ACGTA 144 0 b_bv n 46 y n y y y n n n n y y 1 y bv n n n n n n n n n n n n n NA bbv_n_0
194 | 224bbv AGTA-CACTAC 144 1 b_bv n 46 y n y y n ND ND n y y n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
195 | 225bbv AGTA-TGAC 145 0 b_bv y 34 y n y n y y n n n y y 1 y bv n n n n y n n n n n n n L_salivarius NA bbv_y_0
196 | 226bbv AGTA-AGTA 145 1 b_bv y 34 y n y n n ND ND n n n n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
197 | 227bbv AGTA-ATGA 146 0 b_bv n 24 n n n n y n n y y y y 1 ND bv n n n n n n n n n n n n L_fermentum NA bbv_n_0
198 | 228bbv AGTA-TGCA 146 1 b_bv n 24 n n n n y ND ND n y n y 1 ND i n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
199 | 229bbv AGTA-ACT 147 0 b_bv n 34 n n n n y n n n y y y 1 y bv n n n n y n n n n n n n n NA bbv_n_0
200 | 230bbv AGTA-TCG 147 1 b_bv n 34 n n n n n ND ND n n n y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
201 | 231bbv AGTA-GTA 148 0 b_bv y 45 y n y y y n n n n y y 1 y bv n n n n n n n L_brevis n n n n n NA bbv_y_0
202 | 232bbv AGTA-CTA 148 1 b_bv y 45 y n y y n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
203 | 233bbv AGTA-GAGG 149 0 b_bv n 42 n n y y y n n n n y y 1 y bv n n n n n n n L_plantarum n n n n n NA bbv_n_0
204 | 234bbv AGTA-GAAG 149 1 b_bv n 42 n n y y y ND ND n n y y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
205 | 235bbv AGTA-ATT 150 0 b_bv y 44 n n n n y n n n n y y 1 y bv n n n n n n n L_plantarum n y n n n NA bbv_y_0
206 | 236bbv AGTA-AGG 150 1 b_bv y 44 n n n n n ND ND n n n n 1 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
207 | 237bbv AGTA-AGCC 151 0 b_bv y 19 y y y n y n n n n y y 0 y bv n n n n n n n n n n n n n NA bbv_y_0
208 | 238bbv AGTA-GACC 151 1 b_bv y 19 y y y n n ND ND n n n n 0 ND i n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
209 | 239bbv AGTA-CCTT 152 0 b_bv y 18 y y n n y n n n n y y 1 n bv n y n n y n n n n y n n n NA bbv_y_0
210 | 240bbv AGTA-CGTTG 152 1 b_bv y 18 y y n n n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
211 | 241bbv ATGA-CATGCG 153 0 b_bv y 26 n n y n y n n n n y y 1 y bv n n n n n n n L_reut n n n n n NA bbv_y_0
212 | 242bbv ATGA-GCAGT 153 1 b_bv y 26 n n y n n ND ND n n n n 0 ND n p y n C_parapsilosis NA NA NA NA NA NA NA NA NA NA bbv_y_1
213 | 243bbv ATGA-TAGCT 154 0 b_bv y 42 y n y n y n n n y y y 1 y bv n n n n n n n L_reut n n n n n NA bbv_y_0
214 | 244bbv ATGA-GACTGT 154 1 b_bv y 42 y n y n n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
215 | 245bbv ATGA-CGTCGA 155 0 b_bv y 20 y y n y y n n n n y y 1 y bv n n n n y n n n y n n n n NA bbv_y_0
216 | 246bbv ATGA-GTCGC 155 1 b_bv y 20 y y n y n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
217 | 247bbv ATGA-ACGTA 156 0 b_bv n 19 n n n n y n n n y y y 1 y bv n n n n n n n n n n n n n NA bbv_n_0
218 | 248bbv ATGA-CACTAC 156 1 b_bv n 19 n n n n n ND ND n n y y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
219 | 249bbv ATGA-TGAC 157 0 b_bv n 40 y n y n y n n n n y y 1 y bv n n n n n n n L_brevis n n n n n NA bbv_n_0
220 | 250bbv ATGA-AGTA 157 1 b_bv n 40 y n y n n ND ND n n n n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
221 | 251bbv ATGA-ATGA 158 0 b_bv n 28 y y n n y n y y y y y 0 y bv n n n n n n n n n n n n n NA bbv_n_0
222 | 252bbv ATGA-TGCA 158 1 b_bv n 28 y y n n n ND ND n n n y 0 ND i n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
223 | 253bbv ATGA-ACT 159 0 b_bv n 32 n n y n y y y n y y y 1 y bv n n n n n n n n n n n n n NA bbv_n_0
224 | 254bbv ATGA-TCG 159 1 b_bv n 32 n n y n n ND ND y n n n 0 ND i n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
225 | 255bbv ATGA-GTA 160 0 b_bv y 25 y n y n y y y n n y y 1 y bv n n n n n n n n n n n n n NA bbv_y_0
226 | 256bbv ATGA-CTA 160 1 b_bv y 25 y n y n n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
227 | 257bbv ATGA-GAGG 161 0 b_bv n 27 y y n n n n n n n y y 1 y bv n n n n n n n n y n n n n NA bbv_n_0
228 | 258bbv ATGA-GAAG 161 1 b_bv n 27 y y n n n ND ND n n y y 1 ND i n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
229 | 259bbv ATGA-ATT 162 0 b_bv y 29 n n y y y n y y y y y 1 y bv n n n n n n n n n n n n n NA bbv_y_0
230 | 260bbv ATGA-AGG 162 1 b_bv y 29 n n y y n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
231 | 261bbv ATGA-AGCC 163 0 b_bv n 24 n n y y y n n n y y y 1 y bv n y n n n n n n n n n n n NA bbv_n_0
232 | 262bbv ATGA-GACC 163 1 b_bv n 24 n n y y n ND ND n y y n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
233 | 263bbv ATGA-CCTT 164 0 b_bv n 30 y n n n y n n n n y y 0 y bv n y n n n n n L_plantarum-L_reuteri n n y n n NA bbv_n_0
234 | 264bbv ATGA-CGTTG 164 1 b_bv n 30 y n n n n ND ND n n n n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
235 | 265bbv TGCA-CATGCG 165 0 b_bv y 48 n n n n y n n n n y y 1 y bv n n n n y n n n n n n n n NA bbv_y_0
236 | 266bbv TGCA-GCAGT 165 1 b_bv y 48 n n n n n ND ND n n n n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
237 | 267bbv TGCA-TAGCT 166 0 b_bv n 20 n n n y y n n n y y y 1 y bv n y n n y n n n y n n n n NA bbv_n_0
238 | 268bbv TGCA-GACTGT 166 1 b_bv n 20 n n n y y ND ND n n y y 1 ND bv p y n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
239 | 269bbv TGCA-CGTCGA 167 0 b_bv n 33 y y y n y n n n n y y 1 y bv n n n n y n n n n n y n n NA bbv_n_0
240 | 270bbv TGCA-GTCGC 167 1 b_bv n 33 y y y n y ND ND n n y y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
241 | 271bbv TGCA-ACGTA 168 0 b_bv n 50 n n n n y n n n n y y 1 y bv n n n n y n n n n n n n n NA bbv_n_0
242 | 272bbv TGCA-CACTAC 168 1 b_bv n 50 n n n n n ND ND n n n y 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
243 | 273bbv TGCA-TGAC 169 0 b_bv n 24 y n n n y y y n n y y 1 y bv n n n n y n n n n n n n n NA bbv_n_0
244 | 274bbv TGCA-AGTA 169 1 b_bv n 24 y n n n n ND ND n n n y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
245 | 275bbv TGCA-ATGA 170 0 b_bv y 30 y n n n y n n n n y y 1 y bv n n n n y n n n n n n n n NA bbv_y_0
246 | 276bbv TGCA-TGCA 170 1 b_bv y 30 y n n n n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
247 | 277bbv TGCA-ACT 171 0 b_bv n 17 n n n n y y n n y y y 1 y bv n n n n y n n n n n y n n NA bbv_n_0
248 | 278bbv TGCA-TCG 171 1 b_bv n 17 n n n n n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
249 | 279bbv TGCA-GTA 172 0 b_bv y 27 y n y n y n n n n y y 1 y bv n n n n n n n n n n n n n NA bbv_y_0
250 | 280bbv TGCA-CTA 172 1 b_bv y 27 y n y n n ND ND n n n n 1 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
251 | 281bbv TGCA-GAGG 173 0 b_bv y 29 y y y n n n n n n y y 1 y bv n n n n n n n L_johnsonii y n n n n NA bbv_y_0
252 | 282bbv TGCA-GAAG 173 1 b_bv y 29 y y y n n ND ND n n n y 1 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
253 | 283bbv TGCA-ATT 174 0 b_bv y 21 y y y n y y n n y y y 1 y bv n n n n n n n n y n n n n NA bbv_y_0
254 | 284bbv TGCA-AGG 174 1 b_bv y 21 y y y n n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
255 | 285bbv TGCA-AGCC 175 0 b_bv y 25 n n y n y n n n n y y 1 y bv n n n n y n n n n n n n n NA bbv_y_0
256 | 286bbv TGCA-GACC 175 1 b_bv y 25 n n y n n ND ND n n n y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
257 | 287bbv TGCA-CCTT 176 0 b_bv y 23 y y y y y n n n n y y 1 y bv n n n n y n n n n n n n n NA bbv_y_0
258 | 288bbv TGCA-CGTTG 176 1 b_bv y 23 y y y y n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
259 | 289bbv ACT-CATGCG 177 0 b_bv y 34 y y y n y n n n n y y 1 y bv n n n n n n n n n n n n L_reuteri NA bbv_y_0
260 | 290bbv ACT-GCAGT 177 1 b_bv y 34 y y y n n ND ND n n n n 1 ND n p n n C_glabrata NA NA NA NA NA NA NA NA NA NA bbv_y_1
261 | 291bbv ACT-TAGCT 178 0 b_bv n 46 n n y n y n n n n y y 1 y bv n n n n n n n n n n n n n NA bbv_n_0
262 | 292bbv ACT-GACTGT 178 1 b_bv n 46 n n y n y ND ND n n y y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
263 | 293bbv ACT-CGTCGA 179 0 b_bv y 27 y y y n y n n n y y y 0 y bv n n n n y n n n n n n n L_reuteri NA bbv_y_0
264 | 294bbv ACT-GTCGC 179 1 b_bv y 27 y y y n n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
265 | 295bbv ACT-ACGTA 180 0 b_bv y 26 y n y n y n n n n y y 1 y bv n n n n y n n n n n n n L_rhamnosus NA bbv_y_0
266 | 296bbv ACT-CACTAC 180 1 b_bv y 26 y n y n y ND ND n n y y 0 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
267 | 297bbv ACT-TGAC 181 0 b_bv n 30 y n y n n y n n y y y 1 y bv n n n n n n n L_johnsonii n n n n n NA bbv_n_0
268 | 298bbv ACT-AGTA 181 1 b_bv n 30 y n y n n ND ND n n n n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
269 | 299bbv ACT-ATGA 182 0 b_bv y 21 y y y y y n n n n y y 1 y bv n n n n n n n n n n n n n NA bbv_y_0
270 | 300bbv ACT-TGCA 182 1 b_bv y 21 y y y y n ND ND n n y y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
271 | 301bbv ACT-ACT 183 0 b_bv y 50 n n n n y n n n n y y 1 y bv n n n n y n n no n n n y no NA bbv_y_0
272 | 302bbv ACT-TCG 183 1 b_bv y 50 n n n n n ND ND n n y y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
273 | 303bbv ACT-GTA 184 0 b_bv y 19 y n y n n n n n n y y 1 y bv n n n n n n n no n n n n no NA bbv_y_0
274 | 304bbv ACT-CTA 184 1 b_bv y 19 y n y n n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
275 | 305bbv ACT-GAGG 185 0 b_bv n 19 n n y n y n n n n y y 1 y bv n n n n n n n no n n n n no NA bbv_n_0
276 | 306bbv ACT-GAAG 185 1 b_bv n 19 n n y n n ND ND n n y y 1 ND i n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
277 | 307bbv ACT-ATT 186 0 b_bv n 16 n n y n y n n n n y y 1 y bv n n n n y n n no n n n n no NA bbv_n_0
278 | 308bbv ACT-AGG 186 1 b_bv n 16 n n y n y ND ND n n y y 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
279 | 309bbv ACT-AGCC 187 0 b_bv n 50 n n n n y n y n n y y 1 y bv n n n n n n n no n n n n no NA bbv_n_0
280 | 310bbv ACT-GACC 187 1 b_bv n 50 n n n n n ND ND n n y n 1 ND bv n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
281 | 311bbv ACT-CCTT 188 0 b_bv y 51 n n n y y n n n n y y 1 n bv n n n n n n n L_johnsonii n n n n no NA bbv_y_0
282 | 312bbv ACT-CGTTG 188 1 b_bv y 51 n n n y n ND ND y n n n 1 ND i n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
283 | 313bbv TCG-CATGCG 189 0 b_bv y 16 y y y n y n n n n y y 1 y bv n n n n y n n no n n n n no NA bbv_y_0
284 | 314bbv TCG-GCAGT 189 1 b_bv y 16 y y y n y ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
285 | 315bbv TCG-TAGCT 190 0 b_bv y 25 n n y n y n n n n y y 1 y bv n n n n n n n no n n n n no NA bbv_y_0
286 | 316bbv TCG-GACTGT 190 1 b_bv y 25 n n y n y ND ND n n n n 0 ND i n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
287 | 317bbv TCG-CGTCGA 191 0 b_bv y 43 n n n n y n n n n y y 1 y bv n n n n y n n no n n n n no NA bbv_y_0
288 | 318bbv TCG-GTCGC 191 1 b_bv y 43 n n n n n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
289 | 319bbv TCG-ACGTA 192 0 b_bv n 17 y y n n n y n y n y y 0 y bv n n n n n n y no y n n y no NA bbv_n_0
290 | 320bbv TCG-CACTAC 192 1 b_bv n 17 y y n n n ND ND n n n n 0 ND n n n n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
291 | 321bbv TCG-TGAC 193 0 b_bv n 17 y y y n y n n n n y y 1 y bv n y n n y n n no n n n n no NA bbv_n_0
292 | 322bbv TCG-AGTA 193 1 b_bv n 17 y y y n n ND ND n n n n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
293 | 323bbv TCG-ATGA 194 0 b_bv y 16 y n n y y n n n n y y 1 y bv n n n n y n n no n n n n no NA bbv_y_0
294 | 324bbv TCG-TGCA 194 1 b_bv y 16 y n n y n ND ND n n n n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
295 | 325bbv TCG-ACT 195 0 b_bv y 21 y y y n y n n n n y y 1 y bv n n n n n n n no n n n n no NA bbv_y_0
296 | 326bbv TCG-TCG 195 1 b_bv y 21 y y y n n ND ND n n y n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_y_1
297 | 327bbv TCG-GTA 196 0 b_bv n 16 y y y n y n n n n y y 1 y bv n n n n y y n no n y n n no NA bbv_n_0
298 | 328bbv TCG-CTA 196 1 b_bv n 16 y y y n n ND ND y n y n 0 ND n p y n n NA NA NA NA NA NA NA NA NA NA bbv_n_1
299 |
--------------------------------------------------------------------------------
/inst/shiny-app/extrainformation.Rmd:
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1 | # Extra Information
2 |
3 | ### Principal Component Analysis (PCA) plot
4 |
5 | The PCA plot can show whether your samples separate into groups, what taxa (or groups of tax) are driving this separation, and what taxa are irrelevant for your analysis. More information about how to interpret PCA plots and how they can be used can be found [here](https://github.com/ggloor/CoDa_microbiome_tutorial/blob/master/first_biplot.pdf).
6 |
7 | #### Filtering options
8 |
9 | There are several ways you can filter your data before a biplot is made. The effect of the first slider ('Read Cutoff') is changed by which button is selected. Presence (or absence) of the taxonomy column does not influence the filtering.
10 |
11 | 1. **Minimum count per OTU**
12 | This filter removes any rows with a maximum count with less than the filter.
13 |
14 | 2. **Minimum count sum per sample**
15 | This filter removes any columns that have a lower total sum of counts than the filter.
16 |
17 | 3. **Minimum proportional abundance**
18 | This filter calculates frequency for each sample, and removes any rows that have no frequencies above the threshold (ie, all samples for one OTU have abundance less than 0.01).
19 |
20 | 4. **Maximum proportional abundance**
21 | This filter calculates frequency for each sample, and removes any rows that have no frequencies below the threshold (ie, all samples for one OTU have abundance less than 0.01).
22 |
23 | 5. **Minimum count sum per OTU**
24 | This filter removes any rows that have a lower total sum of counts than the filter.
25 |
26 | **Variance cutoff**
27 |
28 | This filter calculates the variance for each OTU (row), and removes any rows that have lower variance than the filter. Variance is calculated after the reads have been transformed by the centre-log ratio.
29 |
30 | **Adjust scale**
31 |
32 | This changes the scale of the biplot. When set to zero, it shows the relationship between samples (columns), while being set to 1 shows the relationship between OTUs (rows). Data is not filtered from this operation.
33 |
34 | ### Relative Abundance Plots
35 |
36 | A dendrogram and stacked barplot calculates the sum of counts based on genera, showing the relative abundance of each genera for each sample, colour coded by taxonomy. For this to work, you must have a taxonomy column that has at least 6 taxonomic levels. Different method of calculating the distance matrix and. Information about the different clustering methods are available under the details section [of this article.](https://stat.ethz.ch/R-manual/R-devel/library/stats/html/hclust.html)
37 |
38 | ### Effect plots
39 |
40 | Effect plots are useful at showing the size of effect for between group differences. It differs from a Volcano plot, since the effect size is plotted rather than the p-value, giving information about the size of the effect. [Gloor et al. 2016](http://dx.doi.org/10.1080/10618600.2015.1131161) details the differences between effect plots and volcano plots, and what information you can actually obtain from them.
41 |
42 | By hovering your mouse of points on the plot, the sample ID and information will be displayed.
43 |
44 | ### Example data
45 |
46 | Two published example datasets are available to use in omicplotR. The vaginal dataset contains data and metadata, published by [Macklaim et al. (2015).](http://www.tandfonline.com/doi/full/10.3402/mehd.v26.27799)
47 |
48 | The 'selex' dataset contains a dataset without metadata, published by [McMurrough et al. (2014)](http://www.pnas.org/content/111/23/E2376.abstract). When generating effect plots using this data, the first 7 columns are selective conditions and the next 7 columns are grown under non-selective conditions (so enter both conditions manually as 7 columns).
49 |
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/inst/shiny-app/help.Rmd:
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1 | ### Welcome to omicplotR!
2 |
3 | omicplotR is a data visualization tool based on the Shiny framework to easily explore your multivariate 'omic' data.
4 |
5 |
6 |
7 |
8 | #### *Features*
9 |
10 | * Clustering using PCA biplots
11 | * Filtering count tables by counts (per sample or OTU/gene)
12 | * Filter data using metadata
13 | * Colouring biplots using metadata
14 | * Dendrograms and stacked barplots for taxonomic information
15 | * Interactive effect plots using ALDEx2
16 |
17 |
18 | #### *Data format requirements*
19 |
20 | **Data**
21 |
22 | 1. The data file must be a **tab delimited .txt** (this is an option when you click 'Save as' from Excel).
23 | 2. The first column must contain gene/OTU identifier.
24 | 3. The first row must contain sample identifiers.
25 | 4. The last column may contain taxonomic level information, but is not required. If present, it must be labelled 'taxonomy'.
26 | 5. Data table must have all blank rows removed (this may require you to check in a text editor like Notepad ++ or Atom before using the app)
27 |
28 |
29 | **Metadata**
30 |
31 | 1. Must be a **tab delimited .txt** (this is an option when you click 'Save as' from Excel).
32 | 2. The first column must contain sample identifiers. The sample identifiers must be identical to the data file (not required to be in the same order).
33 | 3. The first row must contain phenotypic information.
34 |
35 |
36 |
37 | #### Saving Plots
38 |
39 | To save your image, right-click the desired image and click 'Save picture as'.
40 |
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/inst/shiny-app/rab_script.R:
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1 | #script for reproducing the dendrogram and relative abundance stacked barplots. values chosen for filtering in omicplotR are listed above
2 | #all omicplotr functions can be found in inst/shiny-app/internal.r
3 |
4 | library(zCompositions)
5 | library(ALDEx2)
6 | library(omicplotR)
7 |
8 | ##################################################################
9 | # #
10 | # You must change the file variable to your own file name #
11 | # #
12 | # #
13 | ##################################################################
14 |
15 | #change filename.txt to your filename, make sure it follow input requirements
16 | file <- "filename.txt"
17 |
18 | data <- read.table(
19 | file,
20 | header = TRUE,
21 | sep = "\t",
22 | stringsAsFactors = FALSE,
23 | quote = "",
24 | row.names = 1,
25 | check.names = FALSE,
26 | comment.char = "",
27 | na.strings = "")
28 |
29 | #filter data
30 | x.filt <- omicplotr.filter(data, min.reads = min.reads, min.count = min.count, min.prop = min.prop, max.prop = max.prop, min.sum = min.sum)
31 |
32 | #check for taxonomy column, get taxonomy if present
33 | if (is.null(x.filt$taxonomy)) {
34 | print("Taxonomy column required")
35 | } else {
36 | d <- x.filt[, seq_along(x.filt) - 1]
37 | taxon <- x.filt[(dim(x.filt)[2])]
38 | }
39 |
40 | # Get genera
41 | genera <- c()
42 | for(i in (seq_len(nrow(taxon)))) {
43 | genera <- c(genera, vapply(strsplit(as.character(taxon[i, ]), "[[:punct:]]"),
44 | "[", 6, FUN.VALUE=character(1)))
45 | }
46 |
47 | # sum counts by name
48 | d.agg <- aggregate(d, by=list(genera), FUN=sum)
49 | tax.agg <- d.agg$Group.1
50 | d.agg$Group.1 <- NULL
51 |
52 | # convert to abundances
53 | d.prop <- apply(d.agg, 2, function(x){x/sum(x)})
54 |
55 | #filters by abundance (slider bar)
56 | d.abund <- d.agg[apply(d.prop, 1, max) > abund,]
57 | tax.abund.u <- tax.agg[apply(d.prop, 1, max) > abund]
58 |
59 | d.abund <- t(cmultRepl(t(d.abund), label=0, method="CZM"))
60 |
61 | # get proportions of the filtered data for plotting below
62 | # in log-ratio speak, you are re-closing your dataset
63 | d.P.u <- apply(d.abund, 2, function(x){x/sum(x)})
64 |
65 | # order by OTU abundances
66 | new.order <- rownames(d.P.u)[order(apply(d.P.u, 1, sum), decreasing=TRUE)]
67 | tax.abund <- tax.abund.u[order(apply(d.P.u, 1, sum), decreasing=TRUE)]
68 | d.P <- d.P.u[new.order, ]
69 | d.clr <- apply(d.P, 2, function(x){log2(x) - mean(log2(x))})
70 |
71 | #distance matrix
72 | method.m <- c("euclidean", "maximum", "manhattan")
73 | method.mchoice <- method.m[dist]
74 |
75 | dist.d.clr <- dist(t(d.clr), method=method.mchoice)
76 |
77 | #get clustering method for dendrogram
78 | method <- c("complete", "single", "ward.D2")
79 | method.choice <- method[clust]
80 |
81 | clust.d <- hclust(dist.d.clr, method=method.choice)
82 |
83 | #plot the dendrogram (option for wide pdfs below)
84 | plot(as.dendrogram(clust.d), main=NULL, cex=0.8, xlab="", xpd = TRUE)
85 |
86 | #change colours if you'd like
87 | colours <- c("steelblue3", "skyblue1", "indianred", "mediumpurple1",
88 | "olivedrab3", "pink", "#FFED6F", "mediumorchid3",
89 | "ivory2", "tan1", "aquamarine3", "#C0C0C0", "royalblue4",
90 | "mediumvioletred", "#999933", "#666699", "#CC9933", "#006666",
91 | "#3399FF", "#993300", "#CCCC99", "#666666", "#FFCC66",
92 | "#6699CC", "#663366", "#9999CC", "#CCCCCC", "#669999",
93 | "#CCCC66", "#CC6600", "#9999FF", "#0066CC", "#99CCCC",
94 | "#999999", "#FFCC00", "#009999", "#FF9900", "#999966",
95 | "#66CCCC", "#339966", "#CCCC33", "#EDEDED")
96 |
97 | #relative abundance barplot
98 | plot.new()
99 |
100 | #change sizing so barplot and legend fit
101 | par(fig=c(0,1,0,1), new = TRUE)
102 | par(fig=c(0,0.80,0, 1), new = TRUE)
103 |
104 | #stacked barplot
105 | barplot(d.P[,clust.d$order], names.arg = clust.d$labels, space=0, col=colours, las=2, axisnames=TRUE, border = NA, xpd = TRUE)
106 |
107 | #change location of legend
108 | par(fig=c(0.8,1, 0, 1), new=TRUE)
109 | par(xpd = TRUE)
110 |
111 | #get legend colours
112 | leg.col <- rev(colours[seq_len(nrow(d.P))])
113 |
114 | #add legend
115 | legend(x="center", legend=rev(tax.abund), col=leg.col, lwd=5, cex=0.8,
116 | border=NULL)
117 |
118 | ######## option for wide pdfs
119 |
120 | #approximate width for clear sample names, change if too wide/narrow.
121 | #remove hash tags and enter into R.
122 |
123 | ######## dendrogram
124 | #wid <- round(length(clust.d$labels)/5)
125 | #pdf("omicplotR_dendrogram.pdf", width = wid)
126 | #plot(as.dendrogram(clust.d), main=NULL, cex=0.8, xlab="", xpd = T)
127 | #dev.off()
128 |
129 | ######## barplot
130 | # wid <- round(length(clust.d$labels)/5)
131 | # pdf("omicplotR_rab_barplot.pdf", width = wid)
132 | # #change sizing so barplot and legend are on same graph
133 | # par(fig=c(0,1,0,1), new = TRUE)
134 | # par(fig=c(0,0.80,0, 1), new = TRUE)
135 | #
136 | # #stacked barplot
137 | # barplot(d.P[,clust.d$order], names.arg = clust.d$labels, space=0, col=colours, las=2, axisnames=T, border = NA, xpd = T)
138 | #
139 | # #change location of legend
140 | # par(fig=c(0.8,1, 0, 1), new=TRUE)
141 | # par(xpd = TRUE)
142 | #
143 | # #get legend colours
144 | # leg.col <- rev(colours[seq_len(nrow(d.P))])
145 | #
146 | # #add legend
147 | # legend(x="center", legend=rev(tax.abund), col=leg.col, lwd=5, cex=0.8,
148 | # border=NULL)
149 | # dev.off()
150 |
151 | ########
152 | ################################################################################
153 |
--------------------------------------------------------------------------------
/inst/shiny-app/ui.r:
--------------------------------------------------------------------------------
1 | #in R studio, click Run App (Run External in browser)
2 |
3 | #userinterface -------------------------------------------------------
4 | ui <- fluidPage(theme= "bootstrap.css",
5 | titlePanel("omicplotR: Visual exploration of omic datasets as compositions"),
6 |
7 | navbarPage("omicplotR",
8 | tabPanel("Getting started",
9 | fluidRow(
10 | column(6, offset = 3, includeMarkdown("help.Rmd")
11 | )
12 | )
13 | ),
14 | tabPanel("Input data",
15 | sidebarLayout(
16 | sidebarPanel(
17 | tabsetPanel(
18 | type = "tabs",
19 | selected = "Data",
20 | tabPanel(
21 | "Data",
22 | fluidRow(
23 | column(6, fileInput(
24 | 'file1',
25 | label = h3('Choose Data'))
26 | ),
27 | column(6, fileInput(
28 | 'file2',
29 | h3('Choose Metadata'),
30 | accept = c('text/csv',
31 | 'text/comma-separated-values,text/plain', '.csv'))
32 | )), #fluidrow
33 | checkboxInput("ebi_format", "Click if data is being downloaded from the MGnify datase"),
34 | h3(textOutput("EBI_data")),
35 | #input EBI project
36 | fluidRow(
37 | column(6, h3(actionButton("input_ebi_project", "Download dataset from EBI")))
38 | ),
39 | fluidRow(
40 | column(6, actionButton("showdata", "Check data")),
41 | column(6, actionButton("showmetadata", "Check metadata"))
42 | )
43 | ), #tabpanel
44 | tabPanel(
45 | "Example Data",
46 | checkboxInput("exampledata", "Vaginal dataset (data and metadata)"),
47 | checkboxInput("exampledata2", "Selex dataset (data only)")
48 | )
49 | )
50 | ),#sidebarpanel
51 | mainPanel(
52 | tabsetPanel(
53 | type = "tabs",
54 | selected="Data",
55 | tabPanel("Data",
56 | DT::dataTableOutput('datatable')
57 | ),
58 | tabPanel("Metadata",
59 | DT::dataTableOutput("metadatatable")
60 | )
61 | ))
62 | )
63 | ),#tabpanel
64 | tabPanel("PCA Biplots",
65 | sidebarLayout(
66 | sidebarPanel(
67 | tabsetPanel(
68 | type = "tabs",
69 | selected = "Filtering",
70 | tabPanel("Filtering",
71 | h3(textOutput("textTitle")),
72 | fluidRow(column(6, numericInput("mincounts", "Minimum count per OTU", value = 0)),
73 | column(6, numericInput("minreads", "Minimum count sum per sample", value = 0))),
74 | fluidRow(column(6, numericInput("minprop", "Minimum proportional abundance", value = 0.0)),
75 | column(6, numericInput("maxprop", "Maximum proportional abundance", value = 1))),
76 | fluidRow(column(6, sliderInput("minsum", "Minimum count sum per OTU", min = 0, max = 10000, value = 1)),
77 | column(6, uiOutput("varianceslider"))),
78 | fluidRow(column(6, sliderInput(
79 | inputId = "scale",
80 | label = "Adjust scale (0 = between samples, 1 = between OTUs)",
81 | value = 0,
82 | min = 0,
83 | max = 1,
84 | step = 1
85 | )),
86 | downloadButton("PCA_download", "Download script")),
87 |
88 | # sliderInput("minsum", "Minimum count sum per OTU", min = 0, max = 10000, value = 1),
89 | # uiOutput("varianceslider"),
90 | # sliderInput(
91 | # inputId = "scale",
92 | # label = "Adjust scale (0 = between samples, 1 = between OTUs)",
93 | # value = 0,
94 | # min = 0,
95 | # max = 1,
96 | # step = 1
97 | # ),
98 | # downloadButton("PCA_download", "Download script"),
99 | textOutput("removedsamples"),
100 | textOutput("removedotus")
101 | ),
102 | tabPanel("Options",
103 | uiOutput("choose_column"),
104 | radioButtons(
105 | label = h4("Choose data type"),
106 | inputId = "colouringtype",
107 | choices = list(
108 | "Continuous colouring" = 1,
109 | "Quartile" = 2,
110 | "Nonnumeric metadata (up to 10 categories)" = 3
111 | )
112 | ),
113 | radioButtons(
114 | label = h4("Choose zero replacement method"),
115 | inputId= "zero_replacement",
116 | choices = list(
117 | "Count zero multiplicative (CZM)" = 1,
118 | "Pseudocount (+ 0.5)" = 2)
119 | ),
120 | #change graphical parameters
121 | #size of sample names
122 | fluidRow(column(6, sliderInput("size_samples_pca", label = "Size of sample names", min = 0, max = 2, value = 1.0, step = 0.1)),
123 | column(6, sliderInput("opacity_samples_pca", label = "Opacity of sample names", min = 0, max = 1, value = 1.0, step = 0.05))),
124 | actionButton("choosemeta", "Filter by metadata values"),
125 | textOutput("test"),
126 | checkboxInput("removesamplenames", label = "Remove sample names"),
127 | checkboxInput("arrowcheckbox", label = "Add arrows", value = FALSE),
128 | checkboxInput("taxoncheckbox", label = "Show taxonomy", value = FALSE),
129 | uiOutput("taxchoice")
130 | #,
131 | #textInput("biplot_title", label = "Biplot title", placeholder = "Title for biplot")
132 | )
133 | )
134 | ),
135 | mainPanel(
136 | tabsetPanel(
137 | selected = "Biplot",
138 | tabPanel(
139 | "Biplot",
140 | h3(textOutput("nodata")),
141 | splitLayout(
142 | cellWidths = c("60%", "40%"),
143 | plotOutput("biplot", width = 600, height = 600),
144 | plotOutput("screeplot")
145 | )
146 | ),
147 | tabPanel(
148 | "Colored Biplot",
149 | h3(textOutput("nometadata")),
150 | splitLayout(
151 | cellWidths = c("65%", "35%"),
152 | plotOutput("coloredBiplot", width = 600, height = 600),
153 | plotOutput("metahist")
154 | )
155 | ),
156 | tabPanel("Removed data",
157 | fluidRow(
158 | column(6, plotOutput("colsums")),
159 | column(6, plotOutput("rowsums")),
160 | tabsetPanel(tabPanel("Samples removed", fluidRow(column(
161 | 12, DT::dataTableOutput("removedDT")
162 | )),
163 | actionButton("showremoved", "Show removed samples/OTUs")),
164 | tabPanel("Features removed", fluidRow(column(
165 | 12, DT::dataTableOutput("removedDTotu")
166 | ))))
167 | )
168 | )
169 | )))#sidebarlayout
170 | ), #tabpanel
171 | # tabPanel("Association plots",
172 | # sidebarLayout(
173 | # sidebarPanel(width = 3,
174 | # numericInput("rhocutoff",
175 | # label = "Input rho cutoff",
176 | # value = -0.25),
177 | # textOutput("associationtext")),
178 | # mainPanel(plotOutput("associationplot"))
179 | # )),
180 | tabPanel("Relative abundance plots",
181 | sidebarLayout(
182 | sidebarPanel(width = 3,
183 | sliderInput("abundcutoffbarplot", "Choose abundance cutoff", min = 0, max = 0.25, value= 0, step = 0.01),
184 | selectInput("clustermethod", "Select clustering method",
185 | choices = list("complete" = 1, "single" = 2, "ward.D2" = 3), selected = 3),
186 | selectInput("dismethod", "Select distance matrix method",
187 | choices = list("euclidean" = 1, "maximum" = 2, "manhattan" = 3), selected = 1),
188 | textOutput("filter_warning_dendro"),
189 | downloadButton("rab_download", "Download script")
190 | ),
191 | mainPanel(
192 | textOutput("dendrotext"),
193 | plotOutput("dendrogram",
194 | dblclick = "dendro_dblclick",
195 | brush = brushOpts(
196 | id = "dendro_brush",
197 | resetOnNew = TRUE
198 | )),
199 | plotOutput("barplot",
200 | dblclick = "bp_dblclick",
201 | brush = brushOpts(
202 | id = "bp_brush",
203 | resetOnNew = TRUE
204 | ))
205 | )
206 | )
207 | ),
208 | tabPanel("GO slim annotation",
209 | sidebarPanel(width = 2,
210 | checkboxInput("returnpdf", "Output PDF", FALSE),
211 | conditionalPanel(
212 | condition = "input.returnpdf == true",
213 | downloadLink("pdflink"),
214 | textOutput("pdf_note")
215 | )
216 | ),
217 | wellPanel(plotOutput("ebi_stripchart", height = "auto"), style = "overflow-y:scroll")
218 | ),
219 | tabPanel("Effect plots",
220 | sidebarLayout(
221 | sidebarPanel(
222 | tabsetPanel(
223 | tabPanel("Calculate",
224 | radioButtons("ep_chooseconds", "How will you select your conditions?", choices = list("Manually" = 1, "From metadata" = 2)),
225 | conditionalPanel("input.ep_chooseconds =='1'",
226 | actionButton("select_ef_columns", "Select columns for effect plot")),
227 | selectInput("denomchoice", "Choose ALDEx2 method", choices = list("all" = 1, "iqlr" = 2, "zero"= 3)),
228 | actionButton("effectplot_ab", "Generate effect plot"),
229 | # textOutput("anosim"),
230 | conditionalPanel("input.ep_chooseconds == '2'",
231 | uiOutput("colselectcond")),
232 | uiOutput("conditions"),
233 | textOutput("effectwarning"),
234 | textOutput("filter_warning_effect"),
235 | downloadButton("effect_download", "Download script")
236 | ),
237 | tabPanel("Input",
238 |
239 | fileInput(
240 | 'effect_file',
241 | label = h3('Input ALDEx2 file'),
242 | accept = c('text/csv',
243 | 'text/comma-separated-values,text/plain',
244 | '.csv')
245 | ),
246 | actionButton("effectplot_ab2", "Generate effect plot")
247 | )
248 | )
249 | ),
250 | mainPanel(
251 | tabsetPanel(selected = "Calculate",
252 | tabPanel("Calculate",
253 | h3(textOutput("nostripchart"),
254 | splitLayout(
255 | cellWidths = c("50%", "50%"),
256 | plotOutput("stripchart"),
257 |
258 | plotOutput("effectMW",
259 | hover = hoverOpts(id = "mw_hover"))
260 | ),
261 | fluidRow(column(6, offset = 6,
262 | uiOutput("mw_hovertext"),
263 | plotOutput("effectMA",
264 | hover = hoverOpts(
265 | id = "ma_hover"
266 | )),
267 | uiOutput("ma_hovertext"))
268 | ))),
269 | tabPanel("ALDEx2 input",
270 | splitLayout(
271 | cellWidths = c("50%", "50%"),
272 | plotOutput("table_effect",
273 | hover = hoverOpts(id = "mw_hover2")),
274 | plotOutput("table_bland",
275 | hover = hoverOpts(
276 | id = "ma_hover"
277 | ))
278 | ),
279 | uiOutput("featurename"),
280 | textInput("point.colour", label = "Colour points by name",
281 | placeholder = "Input string to search in row names..."
282 | ),
283 | actionButton("update_points", label = "Update")
284 | )
285 | )
286 | ))),
287 | navbarMenu("More",
288 | tabPanel("Instructions",
289 | fluidRow(
290 | (column(6, offset = 3, includeMarkdown("extrainformation.Rmd")))
291 | )
292 | ),
293 | tabPanel("Quit omicplotR",
294 | actionButton("stopApp", label="Quit omicplotR")
295 | ) #tab panel
296 | ) #navbar menu
297 | )
298 | )
299 |
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/man/internal.Rd:
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1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/internal.R
3 | \name{internal}
4 | \alias{omicplotr.anosim}
5 | \alias{omicplotr.clr}
6 | \alias{omicplotr.colvec}
7 | \alias{omicplotr.filter}
8 | \alias{omicplotr.colouredPCA}
9 | \alias{omicplotr.getRemovedSamples}
10 | \alias{omicplotr.getRemovedFeatures}
11 | \alias{omicplotr.metadataFilter}
12 | \alias{omicplotr.permanova}
13 | \alias{omicplotr.report}
14 | \title{Internal omicplotR functions.}
15 | \description{
16 | Internal functions for the app which are not intended to be called by the
17 | user. Please refer to \link{omicplotr.run}.
18 | }
19 | \examples{
20 | # These functions are not meant to be called by the user. However, some
21 | # functions can be useful.
22 |
23 | data(otu_table)
24 | # Filter out your OTU table to remove rows that sum to less than 10.
25 |
26 | d <- omicplotr.filter(otu_table, min.reads = 10)
27 |
28 | }
29 | \author{
30 | Daniel Giguere, Greg Gloor.
31 | }
32 |
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/man/metadata.Rd:
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1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/metadata.r
3 | \docType{data}
4 | \name{metadata}
5 | \alias{metadata}
6 | \title{Vaginal microbiome OTU table metadata}
7 | \format{A data frame with 297 rows and 35 columns, where rows are samples
8 | and columns are collected metadata.}
9 | \usage{
10 | data(metadata)
11 | }
12 | \description{
13 | Associated metadata to \code{\link{otu_table}}.
14 | }
15 | \references{
16 | Macklaim et al (2014). Microb Ecol Health Dis.
17 | doi: http://dx.doi.org/10.3402/mehd.v26.27799
18 | }
19 | \seealso{
20 | \code{\link{otu_table}}
21 | }
22 |
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/man/omicplotR-package.Rd:
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1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/omicplotr.R
3 | \docType{package}
4 | \name{omicplotR-package}
5 | \alias{omicplotR}
6 | \alias{omicplotR-package}
7 | \title{\code{omicplotR}}
8 | \description{
9 | A Shiny app for visual exploration of omic datasets as
10 | compositions, and differential abundance analysis using ALDEx2. Useful for
11 | exploring RNA-seq, meta-RNA-seq, 16s rRNA gene sequencing and more with
12 | visualizations such as principal component analysis biplot (coloured using
13 | metadata for visualizing each variable), association plots (igraph),
14 | dendrograms and stacked bar plots, and effect plots (ALDEx2). Input is a
15 | table of counts and metadata file (if metadata exists), with options to
16 | filter data by count or by metadata to remove low counts, or to visualize
17 | select samples according to selected metadata. The Shiny app's graphical
18 | user interface facilitates visual exploration for new and experienced
19 | users of R alike.
20 | }
21 | \details{
22 | To launch the \code{shiny} app in your default browser, type
23 | \code{omicplotr.run()}.
24 | }
25 | \seealso{
26 | \code{\link{omicplotr.run}}.
27 | }
28 | \author{
29 | Daniel Giguere, Jean Macklaim, Greg Gloor
30 | }
31 |
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/man/omicplotr.run.Rd:
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1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/omicplotr.run.R
3 | \name{omicplotr.run}
4 | \alias{omicplotr.run}
5 | \title{Run \code{omicplotR} \code{Shiny} app.}
6 | \usage{
7 | omicplotr.run()
8 | }
9 | \description{
10 | Launches \code{Shiny} for \code{omicplotR} in default browser. This
11 | graphical user interface facilitates visual exploration of datasets for
12 | both new and experienced R users alike.
13 | }
14 | \value{
15 | There is no value!
16 | }
17 | \examples{
18 | # To run omicplotR, use `omicplotr.run()` function. This will open the shiny
19 | # app in your default browser.
20 |
21 | # omicplotr.run()
22 |
23 | # After running omicplotr.run(), you can filter your data and make a PCA
24 | # biplot. Internal functions are not mean to be called by the user.
25 |
26 | data(otu_table)
27 | d.filt <- omicplotr.filter(otu_table)
28 |
29 | }
30 | \author{
31 | Daniel Giguere
32 | }
33 |
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/man/otu_table.Rd:
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1 | % Generated by roxygen2: do not edit by hand
2 | % Please edit documentation in R/otu_table.r
3 | \docType{data}
4 | \name{otu_table}
5 | \alias{otu_table}
6 | \title{Vaginal microbiome OTU table}
7 | \format{A data frame with 77 rows and 298 columns. The last column contains
8 | taxonomic information for each OTU. Samples are columns, OTUs are rows.}
9 | \usage{
10 | data(otu_table)
11 | }
12 | \description{
13 | This dataset contains a count table of operational taxonomic units (OTUs)
14 | from a 16s rRNA gene sequencing experiment characterising changes in
15 | bacterial microbiota from oral antimicrobial or probiotic treatments.
16 | Associated metadata is contained in \code{\link{metadata}}.
17 | }
18 | \references{
19 | Macklaim et al (2014). Microb Ecol Health Dis.
20 | doi: http://dx.doi.org/10.3402/mehd.v26.27799
21 | }
22 |
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/vignettes/omicplotR.Rmd:
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1 | ---
2 | title: "omicplotR: A tool for visualizing omic datasets as compositions"
3 | author: "Daniel Giguere, Jean Macklaim, Greg Gloor"
4 | date: "04-18-2018"
5 | output:
6 | html_document:
7 | toc: true
8 | toc_float: true
9 | toc_depth: 3
10 | vignette: >
11 | %\VignetteIndexEntry{omicplotR: A tool for visualization of omic datasets as compositions}
12 | %\VignetteEngine{knitr::rmarkdown}
13 | %\VignetteEncoding{UTF-8}
14 | ---
15 |
16 | ```{r global_options, include=FALSE}
17 | #makes the figure position be held to its position in the text.
18 | knitr::opts_chunk$set(fig.pos = "h")
19 | ```
20 |
21 | # What is omicplotR?
22 |
23 | `omicplotR` is an R package containing a `Shiny` app used to visually explore omic datasets, where the input is a table of read counts from high-throughput sequencing runs. It integrates the `ALDEx2`[^1] package for compositional analysis of differential abundance. `omicplotR` is intended facilitate exploring high-throughput sequencing datasets by providing a graphical user interface for users with and without experience in R.
24 |
25 | [^1]: Fernandes et al (2013) PLOS ONE https://doi.org/10.1371/journal.pone.0067019
26 |
27 | # Introduction
28 |
29 | High-throughput sequencing (HTS) instruments generate an amount of reads that is constrained by limitations of the sequencing instrument itself, and do not represent the absolute number of DNA molecules in a sample. For example, an Illumina NextSeq can deliver up to 400 million single-end reads, whereas an Illumina MiSeq2 can only deliver up to 15 million single-end reads[^2]. This type of data, which is constrained by an arbitrary or constant sum, is referred to as compositional data, and high-throughput sequencing data must be treated as such[^3]. See `ALDEx2` for more information.
30 |
31 | Although several R packages exist for exploring high-throughput sequencing data, they are typically command line based, which presents a barrier for users without any significant command line or scripting experience. `omicplotR` was created to facilitate the exploratory phase of high-throughput sequencing data analysis allowing the generation of basic exploratory plots automatically with adjustable features and filters.
32 |
33 | [^2]: https://www.illumina.com/systems/sequencing-platforms/nextseq/specifications.html
34 | [^3]: Gloor et al (2017) Front. Microbiol. https://doi.org/10.3389/fmicb.2017.02224
35 |
36 | This vignette provides an overview of the R package `omicplotR` and the input requirements. A tutorial for each component of the `Shiny` app is available on the wiki: [https://github.com/dgiguer/omicplotR/wiki](https://github.com/dgiguer/omicplotR/wiki). `omicplotR` was developed for several types of HTS datasets including RNASeq, meta-RNASeq, and 16s rRNA gene sequencing, and in principle, can be used for nearly any type of data generated by HTS that contains a tables of counts per feature for each sample.
37 |
38 | # Features
39 |
40 | `omicplotR` provides a graphical user interface using the `Shiny` package for the following visualizations for HTS data:
41 |
42 | * Compositional Principal Component Analysis (PCA) biplots
43 | * Dendrograms
44 | * Stacked barplots of relative taxonomic abundance
45 | * Compositional differential abundance analysis
46 |
47 | Additional features include:
48 |
49 | * Filtering count tables per sample or feature by counts
50 | * Filtering data into groups using metadata to compare sub groups within the data
51 | * Colour PCA biplots using metadata (continuously, by quartile, categorical)
52 | * Generate effect plots between groups according to metadata using `ALDEx2`
53 | * Interactive effect plots to visualize difference between and within groups
54 | * Plot pre-calculated `ALDEx2` tables and colour points by rownames for large datasets
55 |
56 | # Installation and example
57 |
58 | Install the latest version of `omicplotR` using `BiocManager`. Make sure you have the newest version of R, `ALDEx2`, and other dependancies. `omicplotR` requires you to have at least R version 3.5. The most up to date version is available at www.github.com/dgiguer/omicplotr/, and is the dev branch.
59 |
60 | First, load the `omicplotR` package. All other dependencies will be loaded automatically. This will launch the `Shiny` app in your default browser. For this vignette, we will be using the example data and metadata provided. Example data and metadata are accessible by `data(otu_table)` and `data(metadata)`. They are also available as .txt files in `~/omicplotR/shiny-app/`.
61 |
62 | ```{r, eval=FALSE}
63 | install.packages("BiocManager")
64 | BiocManager::install("omicplotR")
65 | library(omicplotR)
66 | omicplotr.run()
67 | ```
68 |
69 | After launching the `Shiny` app, click the 'Input data' tab to get started.
70 |
71 | # Input data
72 |
73 | The 'Data' tab on the sidebar panel allows you to choose your own data and metadata by clicking 'Browse'. To follow along with this vignette, please click the 'Example data' tab on the sidebar panel, and click the checkbox for the 'Vaginal dataset'. This dataset, which includes associated metadata, is from a study that characterized the changes in the vaginal microbiome following antibiotic and probiotic treatment by 16s rRNA gene sequencing[^4]. Return to the 'Data' tab on the sidebar panel to view the data and metadata by clicking 'Show data' and 'Show metadata'. The tabs on the main panel allow you to switch between displaying your data and metadata tables.
74 |
75 | ```{r, echo = FALSE, out.width='80%', fig.align='center', fig.cap="Figure 1: Screenshot of input data page. The 'Example data' tab on the sidebar panel provides access to the provided datasets within the Shiny app."}
76 | knitr::include_graphics("inputdata.png")
77 | ```
78 |
79 | ## Data
80 |
81 | When choosing your own data set, input requirements are as follows: for both metadata and data, each sample and feature name (operational taxonomic unit - OTU) **must be unique**. An example of an appropriately formatted data file is shown in Figure 2.
82 |
83 | 1. The data file must be a **tab delimited .txt** (this is an option when you click 'Save as' from Excel, or when writing to a table in R).
84 | 2. The first column must contain feature/OTU identifiers. In this case, they are labelled as numbers.
85 | 3. The first row must contain sample identifiers.
86 | 4. The last column may contain taxonomic level information, but is not required. If present, it must be labelled exactly 'taxonomy'. **The taxonomy column must have at least four levels, separated by a semi colon or colon.**
87 | 5. Data table must have all blank rows removed (this may require you to check in a text editor like Notepad ++ or Atom before using the app). This should be especially checked if you are using a Windows based computer, since they use different line feeds.
88 |
89 | ```{r, echo = FALSE, out.width='80%', fig.align='center', fig.cap="Figure 2: Example data. If taxonomy column is present, it must use the column name 'taxonomy'. Image taken from modified version of Vaginal dataset."}
90 | knitr::include_graphics("./example_data.png")
91 | ```
92 |
93 | Your metadata file must follow a similar format. An example of an appropriate metadata file is shown in Figure 3.
94 |
95 | 1. Must be a **tab delimited .txt** (this is an option when you click 'Save as' from Excel).
96 | 2. The first column must contain sample identifiers. The sample identifiers must be identical to the data file, however, they are not required to be in the same order.
97 | 3. The first row must contain phenotypic information, or descriptions of each variable.
98 |
99 | ```{r, echo = FALSE, out.width='70%', fig.align='center', fig.cap="Figure 3: Example metadata file. Metadata maybe be numerical or categorical. Any blank spaces will be replaced as NA when importing the file. Any values of T or F will be read as TRUE or FALSE. Image taken from modified version of Vaginal dataset."}
100 | knitr::include_graphics("./example_metadata.png")
101 | ```
102 |
103 | ## Example Data
104 |
105 | The 'Example data' tab on the sidebar panel provides access to two example datasets. We will be using the provided 'Vaginal dataset', which contains both an OTU table and associated metadata. The 'Selex dataset' is from a selective growth experiment giving the differential abundance of 1600 enzyme variants[^5]. After selecting the 'Vaginal dataset', return to the 'Data' tab to and click 'Show data' to view the data. You can view the metadata by clicking 'Show metadata' and switching the tab in the main panel to 'Metadata'. Click the 'PCA Biplots' main tab to proceed.
106 |
107 | [^4]: Macklaim et al (2015) Microb. Ecol. Heal. Dis. https://doi.org/10.3402/mehd.v26.27799.
108 | [^5]: McMurrough et al (2014) PNAS doi:10.1073/pnas.1322352111
109 |
110 | # PCA Biplots
111 |
112 | The 'Filtering' tab within the sidebar panel allows you to choose filtering options for your dataset. Colouring options for a coloured PCA biplot are available under the 'Colouring options' tab. The tabs within the main panel allow you to switch between displaying a biplot under 'Biplot', a biplot coloured by metadata under 'Coloured Biplot', and visualizations of the removed samples/features from filtering under the 'Removed data' tab.
113 |
114 | ```{r, echo = FALSE, fig.align='center', fig.cap="Figure 4: Screenshot of coloured PCA biplot."}
115 | knitr::include_graphics("col_PCA.png")
116 | ```
117 |
118 | ## Filtering
119 |
120 | "Reasonable" filtering of sparse features (rows) from your dataset **should not** affect any conclusions made from the PCA biplots. Filtering is exploratory, and should be experimented with to see how removing sparse data affects the structure of your dataset within the PCA biplot. By default, no filtering is applied. We will use a minimum count per OTU filter of 10 for this vignette.
121 |
122 | Under the 'Filtering' tab within the sidebar panel, the following options are available to filter your data.
123 |
124 | 1. **Minimum count per OTU**
125 | This filter removes any rows with a maximum sample count less than the input. It is recommended to remove sparse features. Try setting this filter to 10.
126 |
127 | 2. **Minimum count sum per sample**
128 | This filter removes any columns that have a lower sum of counts than the filter. You can visualize which samples are being removed when applying this filter using the 'Filtering by counts per sample' graph under the 'Removed data' tab.
129 |
130 | 3. **Minimum proportional abundance**
131 | This filter calculates frequency for each sample (by column) after filters 1 and 2 are applied, and removes any rows that have all frequencies below the threshold.
132 |
133 | 4. **Maximum proportional abundance**
134 | This filter calculates frequency for each sample, and removes any rows that have no frequencies below the threshold.
135 |
136 | 5. **Minimum count sum per OTU**
137 | This filter removes any rows that have a lower sum of counts than the filter. You can visualize which rows are removed with the 'Filtering by counts per row' graph under the 'Removed data' tab.
138 |
139 | 6. **Variance cutoff**
140 | This filter calculates the variance for each OTU (row), and removes any rows that have lower variance than the filter. Variance is calculated after all other filters, and after the reads have been transformed by the centre-log ratio.
141 |
142 | 7. **Adjust scale**
143 | This changes the scale of the biplot. When set to zero, it shows the relationship between samples (columns), while being set to 1 shows the relationship between OTUs (rows). Data is not filtered from this operation.
144 |
145 | ## Colouring options
146 |
147 | To view the coloured PCA biplot, click the 'Coloured Biplot' tab within the main panel. Clicking the 'Colouring options' panel within the side bar panel allows you to choose which metadata to colour your plot by. We will be colouring the samples based on whether or not they were positive for bacterial vaginosis as defined by Nugent status. Choose the column 'n_status' to colour the data by Nugent status. You will need to click the 'nonnumeric metadata' radio button since the values of the column are categorical. The sample names that are black (ie, 128bvvc) on the PCA biplot represent samples without metadata.
148 |
149 | ### Filter by metadata
150 |
151 | Under the 'Colouring options' tab in the sidebar panel, click on 'Filter by metadata values' to replot samples belonging to certain groups according to the metadata. This will generate a pop-up (Figure 5). Filter the dataset to replot only the samples at time zero by selecting the 'time' column, and inputting '0' into the text field for Value 1. This should update the coloured PCA biplot to show samples that were taken from time = 0. Click 'Update Filter' to update the filter, or 'Reset Filter' to reset it. **This filter is applied to the data for all other plots (relative abundance, effect plots).**
152 |
153 | ```{r, echo = FALSE, fig.align='center', out.width='50%', fig.cap="Figure 5: Pop-up generated from clicking 'Filter by metadata values'. Select a column and enter values from the column to re-plot only those values. They must match exactly. The filter can be reset or updated."}
154 | knitr::include_graphics("metafilter.png")
155 | ```
156 |
157 | # Relative abundance plots
158 |
159 | Click the 'Relative abundance plots' main tab to continue. The sidebar panel allows you to filter the data by choosing an abundance cutoff, select the clustering method, and select the distance matrix method. The main panel displays a dendrogram above a stacked barplot, and both can be zoomed in by dragging your mouse over a selected region and double clicking.
160 |
161 | Any filtering by metadata will be reflected in the dendrogram and stacked barplot as well.
162 |
163 | # Effect plots
164 |
165 | To generate effect plots, click on the 'Effect plots' main tab. Here, you can choose to calculate the `ALDEx2` table manually (ie, choosing which columns to compare) or by using metadata. For this example, we will use the included metadata to compare samples that were positive for bacterial vaginosis or not according to Nugent status. More information on choosing manually for your own data set is available on the GitHub wiki.
166 |
167 | Click on the 'From metadata' radio button since we are selecting conditions using our metadata. Select the 'n_status' column from metadata. For Group 1 choose 'bv', and for Group 2 choose 'n'. After these have been selected, click the 'Generate effect plot' button. An effect plot and Bland-Altman plot will be generated. For large datasets, this will take a long time. It takes about 10 seconds for the example data, which has 77 features for 297 samples.
168 |
169 | By hovering your cursor over a point on the effect plot, a stripchart of the expected CLR abundance (see `ALDEx2`) for each sample will be shown, allowing you to compare the differences between your samples for a given feature (Figure 6). It also displays information from the effect table generated by `ALDEx2`, such as the effect size, median difference between groups, and median difference within groups.
170 |
171 | ```{r, echo = FALSE, fig.align='center', fig.cap="Figure 6: Screenshot of effect plots. Hovering over a feature's point in the effect plot generates a stripchart to compare the relative abundances calculated by ALDEx2 for each sample."}
172 | knitr::include_graphics("effect.png")
173 | ```
174 |
175 | If you are using your own data and want to select groups by columns, you will need to reorder your file to have the first *n* columns as group 1, and the last *n* columns as group 2.
176 |
177 | When running `omicplotR`, your R console will be be unavailable. To quit the app, click the 'More' main tab and click 'Quit omicplotR'. Alternatively, you can click `command` `.` on Mac.
178 |
179 | # Contributors
180 |
181 | Daniel J Giguere wrote the original `omicplotR` code and designed the `Shiny` app, with help from Brandon Lieng, Jean Macklaim, and Greg Gloor. Brandon Lieng wrote the function `clr.strip()` needed for the strip charts. Jean Macklaim conceptualized this project, contributed ideas for the design, and wrote the original code for the taxonomic distribution and dendrograms. Greg contributed ideas for features, and played a role in designing and implementing `omicplotR`.
182 |
183 | # Version information
184 |
185 | Currently version 0.99.4.
186 |
187 | For more information about how to use `omicplotR`, please visit the wiki on my Github page:
188 |
189 | [https://github.com/dgiguer/omicplotR/wiki](https://github.com/dgiguer/omicplotR/wiki)
190 |
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