├── .gitignore ├── PLSDAbatch_workflow ├── 01-supp_batch_effects_managment.Rmd ├── 02-simulation_study_Gaussian.Rmd ├── 03-simulation_study_negative_binomial.Rmd ├── 04-references.Rmd ├── GeneratedData │ ├── ADselected_50_splsda.txt │ └── HFHSselected_50_splsda.txt ├── SimulationData │ ├── balanced_Gaussian_2batches.rda │ ├── balanced_mnegbinom_2batches.rda │ ├── balanced_mnegbinom_3batches.rda │ ├── unbalanced_Gaussian_2batches.rda │ ├── unbalanced_mnegbinom_2batches.rda │ └── unbalanced_mnegbinom_3batches.rda ├── _bookdown.yml ├── _bookdown_files │ └── PLSDAbatch_workflow_files │ │ ├── figure-html │ │ ├── ADalignment-1.png │ │ ├── ADboxBefore-1.png │ │ ├── ADdensityBefore-1.png │ │ ├── ADheatmap-1.png │ │ ├── ADlm-1.png │ │ ├── ADpca-1.png │ │ ├── ADpcaBefore-1.png │ │ ├── ADprda-1.png │ │ ├── ADr21-1.png │ │ ├── ADr22-1.png │ │ ├── ADupsetR-1.png │ │ ├── HDheatmap-1.png │ │ ├── HDlmm-1.png │ │ ├── HDlmmS-1.png │ │ ├── HDpcaBefore-1.png │ │ ├── HFHSalignment-1.png │ │ ├── HFHSheatmapS-1.png │ │ ├── HFHSlm-1.png │ │ ├── HFHSlmm-1.png │ │ ├── HFHSpca-1.png │ │ ├── HFHSpcaBefore1-1.png │ │ ├── HFHSpcaBefore2-1.png │ │ ├── HFHSpcaBeforeNew1-1.png │ │ ├── HFHSpcaBeforeNew2-1.png │ │ ├── HFHSprda-1.png │ │ ├── HFHSprdaSup-1.png │ │ ├── HFHSr21-1.png │ │ ├── HFHSr22-1.png │ │ ├── HFHSupsetR-1.png │ │ ├── Spongealignment-1.png │ │ ├── Spongeheatmap-1.png │ │ ├── Spongelm-1.png │ │ ├── Spongepca-1.png │ │ ├── SpongepcaBefore-1.png │ │ ├── Spongeprda-1.png │ │ ├── Sponger21-1.png │ │ ├── Sponger22-1.png │ │ ├── SpongeupsetR-1.png │ │ ├── unnamed-chunk-100-1.png │ │ ├── unnamed-chunk-105-1.png │ │ ├── unnamed-chunk-106-1.png │ │ ├── unnamed-chunk-111-1.png │ │ ├── unnamed-chunk-112-1.png │ │ ├── unnamed-chunk-113-1.png │ │ ├── unnamed-chunk-118-1.png │ │ ├── unnamed-chunk-119-1.png │ │ ├── unnamed-chunk-120-1.png │ │ ├── unnamed-chunk-125-1.png │ │ ├── unnamed-chunk-126-1.png │ │ ├── unnamed-chunk-127-1.png │ │ ├── unnamed-chunk-132-1.png │ │ ├── unnamed-chunk-133-1.png │ │ ├── unnamed-chunk-134-1.png │ │ ├── unnamed-chunk-36-1.png │ │ ├── unnamed-chunk-36-2.png │ │ ├── unnamed-chunk-36-3.png │ │ ├── unnamed-chunk-36-4.png │ │ ├── unnamed-chunk-36-5.png │ │ ├── unnamed-chunk-36-6.png │ │ ├── unnamed-chunk-36-7.png │ │ ├── unnamed-chunk-58-1.png │ │ ├── unnamed-chunk-58-2.png │ │ ├── unnamed-chunk-58-3.png │ │ ├── unnamed-chunk-58-4.png │ │ ├── unnamed-chunk-58-5.png │ │ ├── unnamed-chunk-58-6.png │ │ ├── unnamed-chunk-89-1.png │ │ ├── unnamed-chunk-89-2.png │ │ ├── unnamed-chunk-89-3.png │ │ ├── unnamed-chunk-89-4.png │ │ ├── unnamed-chunk-89-5.png │ │ ├── unnamed-chunk-89-6.png │ │ ├── unnamed-chunk-89-7.png │ │ └── unnamed-chunk-99-1.png │ │ └── figure-latex │ │ ├── ADalignment-1.pdf │ │ ├── ADboxBefore-1.pdf │ │ ├── ADdensityBefore-1.pdf │ │ ├── ADheatmap-1.pdf │ │ ├── ADlm-1.pdf │ │ ├── ADpca-1.pdf │ │ ├── ADpcaBefore-1.pdf │ │ ├── ADprda-1.pdf │ │ ├── ADr21-1.pdf │ │ ├── ADr22-1.pdf │ │ ├── ADupsetR-1.pdf │ │ ├── HDheatmap-1.pdf │ │ ├── HDlmm-1.pdf │ │ ├── HDlmmS-1.pdf │ │ ├── HDpcaBefore-1.pdf │ │ ├── HFHSalignment-1.pdf │ │ ├── HFHSheatmapS-1.pdf │ │ ├── HFHSlm-1.pdf │ │ ├── HFHSlmm-1.pdf │ │ ├── HFHSpca-1.pdf │ │ ├── HFHSpcaBefore1-1.pdf │ │ ├── HFHSpcaBefore2-1.pdf │ │ ├── HFHSpcaBeforeNew1-1.pdf │ │ ├── HFHSpcaBeforeNew2-1.pdf │ │ ├── HFHSprda-1.pdf │ │ ├── HFHSprdaSup-1.pdf │ │ ├── HFHSr21-1.pdf │ │ ├── HFHSr22-1.pdf │ │ ├── HFHSupsetR-1.pdf │ │ ├── Spongealignment-1.pdf │ │ ├── Spongeheatmap-1.pdf │ │ ├── Spongelm-1.pdf │ │ ├── Spongepca-1.pdf │ │ ├── SpongepcaBefore-1.pdf │ │ ├── Spongeprda-1.pdf │ │ ├── Sponger21-1.pdf │ │ ├── Sponger22-1.pdf │ │ ├── SpongeupsetR-1.pdf │ │ ├── unnamed-chunk-100-1.pdf │ │ ├── unnamed-chunk-105-1.pdf │ │ ├── unnamed-chunk-106-1.pdf │ │ ├── unnamed-chunk-111-1.pdf │ │ ├── unnamed-chunk-112-1.pdf │ │ ├── unnamed-chunk-113-1.pdf │ │ ├── unnamed-chunk-118-1.pdf │ │ ├── unnamed-chunk-119-1.pdf │ │ ├── unnamed-chunk-120-1.pdf │ │ ├── unnamed-chunk-125-1.pdf │ │ ├── unnamed-chunk-126-1.pdf │ │ ├── unnamed-chunk-127-1.pdf │ │ ├── unnamed-chunk-132-1.pdf │ │ ├── unnamed-chunk-133-1.pdf │ │ ├── unnamed-chunk-134-1.pdf │ │ ├── unnamed-chunk-36-1.pdf │ │ ├── unnamed-chunk-36-2.pdf │ │ ├── unnamed-chunk-36-3.pdf │ │ ├── unnamed-chunk-36-4.pdf │ │ ├── unnamed-chunk-36-5.pdf │ │ ├── unnamed-chunk-36-6.pdf │ │ ├── unnamed-chunk-36-7.pdf │ │ ├── unnamed-chunk-58-1.pdf │ │ ├── unnamed-chunk-58-2.pdf │ │ ├── unnamed-chunk-58-3.pdf │ │ ├── unnamed-chunk-58-4.pdf │ │ ├── unnamed-chunk-58-5.pdf │ │ ├── unnamed-chunk-58-6.pdf │ │ ├── unnamed-chunk-89-1.pdf │ │ ├── unnamed-chunk-89-2.pdf │ │ ├── unnamed-chunk-89-3.pdf │ │ ├── unnamed-chunk-89-4.pdf │ │ ├── unnamed-chunk-89-5.pdf │ │ ├── unnamed-chunk-89-6.pdf │ │ ├── unnamed-chunk-89-7.pdf │ │ └── unnamed-chunk-99-1.pdf ├── _output.yml ├── agis-logo.png ├── book.bib ├── built_in_functions │ └── data_simulation.R ├── data │ ├── HD_data.rda │ └── HFHS_data.rda ├── figures │ ├── data_description.png │ └── function_description.png ├── index.Rmd ├── packages.bib ├── preamble.tex └── style.css ├── README.md └── docs ├── 404.html ├── PLSDAbatch_workflow.epub ├── PLSDAbatch_workflow.pdf ├── PLSDAbatch_workflow.tex ├── PLSDAbatch_workflow_files └── figure-html │ ├── ADalignment-1.png │ ├── ADboxBefore-1.png │ ├── ADdensityBefore-1.png │ ├── ADheatmap-1.png │ ├── ADlm-1.png │ ├── ADpca-1.png │ ├── ADpcaBefore-1.png │ ├── ADprda-1.png │ ├── ADr21-1.png │ ├── ADr22-1.png │ ├── ADupsetR-1.png │ ├── HDheatmap-1.png │ ├── HDlmm-1.png │ ├── HDlmmS-1.png │ ├── HDpcaBefore-1.png │ ├── HFHSalignment-1.png │ ├── HFHSheatmapS-1.png │ ├── HFHSlm-1.png │ ├── HFHSlmm-1.png │ ├── HFHSpca-1.png │ ├── HFHSpcaBefore1-1.png │ ├── HFHSpcaBefore2-1.png │ ├── HFHSpcaBeforeNew1-1.png │ ├── HFHSpcaBeforeNew2-1.png │ ├── HFHSprda-1.png │ ├── HFHSprdaSup-1.png │ ├── HFHSr21-1.png │ ├── HFHSr22-1.png │ ├── HFHSupsetR-1.png │ ├── Spongealignment-1.png │ ├── Spongeheatmap-1.png │ ├── Spongelm-1.png │ ├── Spongepca-1.png │ ├── SpongepcaBefore-1.png │ ├── Spongeprda-1.png │ ├── Sponger21-1.png │ ├── Sponger22-1.png │ ├── SpongeupsetR-1.png │ ├── unnamed-chunk-100-1.png │ ├── unnamed-chunk-105-1.png │ ├── unnamed-chunk-106-1.png │ ├── unnamed-chunk-111-1.png │ ├── unnamed-chunk-112-1.png │ ├── unnamed-chunk-113-1.png │ ├── unnamed-chunk-118-1.png │ ├── unnamed-chunk-119-1.png │ ├── unnamed-chunk-120-1.png │ ├── unnamed-chunk-125-1.png │ ├── unnamed-chunk-126-1.png │ ├── unnamed-chunk-127-1.png │ ├── unnamed-chunk-132-1.png │ ├── unnamed-chunk-133-1.png │ ├── unnamed-chunk-134-1.png │ └── unnamed-chunk-99-1.png ├── batch-effects-management-in-simulation-studies-gaussian-distribution.html ├── batch-effects-management-in-simulation-studies-negative-binomial-distribution.html ├── figures ├── data_description.png └── function_description.png ├── index.html ├── libs ├── anchor-sections-1.1.0 │ ├── anchor-sections-hash.css │ ├── anchor-sections.css │ └── anchor-sections.js ├── gitbook-2.6.7 │ ├── css │ │ ├── fontawesome │ │ │ └── fontawesome-webfont.ttf │ │ ├── plugin-bookdown.css │ │ ├── plugin-clipboard.css │ │ ├── plugin-fontsettings.css │ │ ├── plugin-highlight.css │ │ ├── plugin-search.css │ │ ├── plugin-table.css │ │ └── style.css │ └── js │ │ ├── app.min.js │ │ ├── clipboard.min.js │ │ ├── jquery.highlight.js │ │ ├── plugin-bookdown.js │ │ ├── plugin-clipboard.js │ │ ├── plugin-fontsettings.js │ │ ├── plugin-search.js │ │ └── plugin-sharing.js └── jquery-3.6.0 │ └── jquery-3.6.0.min.js ├── reference-keys.txt ├── references-4.html ├── search_index.json ├── style.css └── supplementary-materials-for-batch-effects-management-in-case-studies.html /.gitignore: -------------------------------------------------------------------------------- 1 | .Rproj.user 2 | .Rhistory 3 | .RData 4 | .Ruserdata 5 | 6 | ## mac 7 | .DS_Store 8 | 9 | ## 10 | PLSDAbatch_workflow/PLSDAbatch_workflow.Rproj 11 | 12 | -------------------------------------------------------------------------------- /PLSDAbatch_workflow/04-references.Rmd: -------------------------------------------------------------------------------- 1 | `r if (knitr::is_html_output()) ' 2 | # References {-} 3 | '` 4 | -------------------------------------------------------------------------------- /PLSDAbatch_workflow/GeneratedData/ADselected_50_splsda.txt: -------------------------------------------------------------------------------- 1 | $`PLSDA-batch` 2 | Kingdom Phylum Class Order 3 | OTU71 Bacteria Firmicutes Clostridia Clostridiales 4 | OTU106 Archaea Euryarchaeota Thermoplasmata Thermoplasmatales 5 | OTU84 Bacteria Firmicutes Clostridia Clostridiales 6 | OTU177 Bacteria Firmicutes Clostridia Clostridiales 7 | Family Genus 8 | OTU71 Ruminococcaceae Ruminiclostridium 9 | OTU106 Thermoplasmatales Incertae Sedis unknown genus 10 | OTU84 Ruminococcaceae Acetanaerobacterium 11 | OTU177 Christensenellaceae Christensenellaceae R-7 group 12 | Species 13 | OTU71 unknown species 14 | OTU106 unknown species 15 | OTU84 unknown species 16 | OTU177 unknown species 17 | 18 | $`sPLSDA-batch` 19 | Kingdom Phylum Class Order 20 | OTU116 Bacteria Firmicutes Clostridia Clostridiales 21 | OTU209 Bacteria Firmicutes Clostridia Clostridiales 22 | OTU216 Bacteria Firmicutes Clostridia Clostridiales 23 | OTU87 Bacteria Firmicutes Clostridia Clostridiales 24 | Family Genus Species 25 | OTU116 Clostridiales vadinBB60 group unknown genus unknown species 26 | OTU209 Peptococcaceae Sporotomaculum Sporotomaculum syntrophicum 27 | OTU216 Family XIV unknown genus unknown species 28 | OTU87 Peptococcaceae Pelotomaculum unknown species 29 | 30 | $`Before correction` 31 | Kingdom Phylum Class Order 32 | OTU110 Bacteria Firmicutes Clostridia Clostridiales 33 | OTU141 Bacteria Firmicutes Clostridia Clostridiales 34 | OTU31 Bacteria Firmicutes Bacilli Bacillales 35 | OTU86 Archaea Euryarchaeota Methanomicrobia Methanomicrobiales 36 | Family Genus Species 37 | OTU110 Lachnospiraceae Anaerosporobacter Multi-affiliation 38 | OTU141 Ruminococcaceae unknown genus unknown species 39 | OTU31 Paenibacillaceae Aneurinibacillus unknown species 40 | OTU86 Methanomicrobiaceae Methanoculleus unknown species 41 | 42 | $`Before correction:ComBat` 43 | Kingdom Phylum Class Order Family 44 | OTU218 Bacteria Firmicutes Clostridia Clostridiales Christensenellaceae 45 | Genus Species 46 | OTU218 Christensenellaceae R-7 group unknown species 47 | 48 | $`PLSDA-batch:sPLSDA-batch` 49 | Kingdom Phylum Class Order Family 50 | OTU225 Bacteria Bacteroidetes Bacteroidia Bacteroidales Marinilabiaceae 51 | OTU17 Bacteria Firmicutes Clostridia Clostridiales Ruminococcaceae 52 | Genus Species 53 | OTU225 unknown genus unknown species 54 | OTU17 Acetivibrio Multi-affiliation 55 | 56 | $`removeBatchEffect:ComBat` 57 | Kingdom Phylum Class Order Family 58 | OTU91 Bacteria Firmicutes Clostridia Clostridiales Peptococcaceae 59 | OTU16 Bacteria Synergistetes Synergistia Synergistales Synergistaceae 60 | OTU85 Bacteria Synergistetes Synergistia Synergistales Synergistaceae 61 | OTU18 Bacteria Firmicutes Clostridia Clostridiales Christensenellaceae 62 | Genus Species 63 | OTU91 unknown genus unknown species 64 | OTU16 unknown genus unknown species 65 | OTU85 unknown genus Multi-affiliation 66 | OTU18 unknown genus unknown species 67 | 68 | $`Before correction:PLSDA-batch` 69 | Kingdom Phylum Class Order Family 70 | OTU223 Bacteria Chloroflexi Anaerolineae Anaerolineales Anaerolineaceae 71 | Genus Species 72 | OTU223 unknown genus anaerobic digester metagenome 73 | 74 | $`Before correction:removeBatchEffect` 75 | Kingdom Phylum Class Order Family 76 | OTU143 Bacteria Spirochaetae Spirochaetes Spirochaetales Spirochaetaceae 77 | OTU211 Bacteria Synergistetes Synergistia Synergistales Synergistaceae 78 | Genus Species 79 | OTU143 Sphaerochaeta unknown species 80 | OTU211 Aminobacterium Aminobacterium colombiense 81 | 82 | $`Before correction:ComBat:PLSDA-batch` 83 | Kingdom Phylum Class Order Family 84 | OTU159 Bacteria Chloroflexi Anaerolineae Anaerolineales Anaerolineaceae 85 | Genus Species 86 | OTU159 unknown genus unknown species 87 | 88 | $`Before correction:PLSDA-batch:sPLSDA-batch` 89 | Kingdom Phylum Class Order Family 90 | OTU105 Bacteria Firmicutes Clostridia Clostridiales Syntrophomonadaceae 91 | Genus Species 92 | OTU105 Syntrophomonas anaerobic digester metagenome 93 | 94 | $`removeBatchEffect:ComBat:PLSDA-batch:sPLSDA-batch` 95 | Kingdom Phylum Class Order Family 96 | OTU19 Bacteria Firmicutes Clostridia Clostridiales Family XIV 97 | OTU41 Bacteria Firmicutes Clostridia Clostridiales Ruminococcaceae 98 | OTU9 Bacteria Firmicutes Clostridia Clostridiales Christensenellaceae 99 | OTU27 Bacteria Firmicutes Clostridia Clostridiales Christensenellaceae 100 | Genus Species 101 | OTU19 unknown genus unknown species 102 | OTU41 unknown genus unknown species 103 | OTU9 Christensenellaceae R-7 group unknown species 104 | OTU27 unknown genus unknown species 105 | 106 | $`Before correction:removeBatchEffect:ComBat:PLSDA-batch` 107 | Kingdom Phylum Class Order Family Genus 108 | OTU117 Bacteria Firmicutes Clostridia B55-F-B-G02 unknown family unknown genus 109 | Species 110 | OTU117 unknown species 111 | 112 | $`Before correction:removeBatchEffect:ComBat:sPLSDA-batch` 113 | Kingdom Phylum Class Order 114 | OTU130 Bacteria Firmicutes Bacilli TSCOR001-H18 115 | OTU145 Bacteria Proteobacteria Deltaproteobacteria Bdellovibrionales 116 | OTU44 Bacteria Planctomycetes Phycisphaerae KCLunmb-38-53 117 | Family Genus Species 118 | OTU130 unknown family unknown genus unknown species 119 | OTU145 Bacteriovoracaceae unknown genus unknown species 120 | OTU44 unknown family unknown genus unknown species 121 | 122 | $`Before correction:removeBatchEffect:ComBat:PLSDA-batch:sPLSDA-batch` 123 | Kingdom Phylum Class Order 124 | OTU46 Bacteria Firmicutes Clostridia Clostridiales 125 | OTU24 Bacteria Firmicutes Clostridia Clostridiales 126 | OTU68 Bacteria Firmicutes Clostridia Clostridiales 127 | OTU59 Bacteria Firmicutes Clostridia Thermoanaerobacterales 128 | OTU28 Bacteria Firmicutes Clostridia Clostridiales 129 | OTU104 Bacteria Firmicutes Clostridia Clostridiales 130 | OTU61 Bacteria Firmicutes Clostridia Clostridiales 131 | OTU35 Bacteria Firmicutes Clostridia Clostridiales 132 | OTU118 Bacteria Firmicutes Clostridia M55-D21 133 | OTU65 Bacteria Firmicutes Clostridia Thermoanaerobacterales 134 | OTU193 Bacteria Firmicutes Clostridia Clostridiales 135 | OTU54 Bacteria Firmicutes Erysipelotrichia Erysipelotrichales 136 | OTU96 Bacteria Firmicutes Clostridia MBA03 137 | OTU88 Bacteria Firmicutes Clostridia Clostridiales 138 | OTU43 Bacteria Firmicutes Clostridia Clostridiales 139 | OTU6 Bacteria Firmicutes Clostridia Clostridiales 140 | OTU62 Bacteria Firmicutes Clostridia Clostridiales 141 | OTU56 Bacteria Firmicutes Clostridia Clostridiales 142 | OTU198 Bacteria Bacteroidetes Bacteroidia Bacteroidales 143 | OTU144 Bacteria Firmicutes Clostridia Clostridiales 144 | OTU23 Bacteria Proteobacteria Deltaproteobacteria Bdellovibrionales 145 | OTU48 Bacteria Firmicutes Clostridia Clostridiales 146 | OTU135 Bacteria Bacteroidetes Bacteroidia Bacteroidales 147 | OTU51 Bacteria Chloroflexi Anaerolineae Anaerolineales 148 | OTU74 Bacteria Firmicutes Clostridia Clostridiales 149 | OTU138 Bacteria Firmicutes Clostridia Clostridiales 150 | OTU205 Bacteria Firmicutes Clostridia Clostridiales 151 | OTU7 Bacteria Bacteroidetes Bacteroidia Bacteroidales 152 | OTU36 Bacteria Firmicutes Clostridia Clostridiales 153 | OTU127 Bacteria Firmicutes Clostridia Clostridiales 154 | OTU151 Bacteria Firmicutes Clostridia Clostridiales 155 | OTU5 Bacteria Bacteroidetes Bacteroidia Bacteroidales 156 | OTU64 Bacteria Firmicutes Clostridia Clostridiales 157 | OTU94 Bacteria Firmicutes Clostridia Clostridiales 158 | OTU76 Bacteria Armatimonadetes Chthonomonadetes Chthonomonadales 159 | OTU248 Bacteria Bacteroidetes Bacteroidia Bacteroidales 160 | Family Genus 161 | OTU46 Ruminococcaceae Ruminiclostridium 162 | OTU24 Gracilibacteraceae Lutispora 163 | OTU68 Family XIV unknown genus 164 | OTU59 Thermoanaerobacteraceae Moorella 165 | OTU28 Heliobacteriaceae Hydrogenispora 166 | OTU104 Peptococcaceae Pelotomaculum 167 | OTU61 Gracilibacteraceae Multi-affiliation 168 | OTU35 Syntrophomonadaceae Syntrophomonas 169 | OTU118 unknown family unknown genus 170 | OTU65 SRB2 unknown genus 171 | OTU193 Lachnospiraceae Tyzzerella 172 | OTU54 Erysipelotrichaceae Erysipelotrichaceae UCG-004 173 | OTU96 unknown family unknown genus 174 | OTU88 Caldicoprobacteraceae Caldicoprobacter 175 | OTU43 Ruminococcaceae Ruminiclostridium 176 | OTU6 Lachnospiraceae Mobilitalea 177 | OTU62 Clostridiales vadinBB60 group unknown genus 178 | OTU56 Christensenellaceae Christensenellaceae R-7 group 179 | OTU198 Marinilabiaceae Ruminofilibacter 180 | OTU144 Clostridiales vadinBB60 group unknown genus 181 | OTU23 Bacteriovoracaceae unknown genus 182 | OTU48 Lachnospiraceae Anaerosporobacter 183 | OTU135 Porphyromonadaceae Proteiniphilum 184 | OTU51 Anaerolineaceae unknown genus 185 | OTU74 Lachnospiraceae unknown genus 186 | OTU138 Ruminococcaceae Ruminiclostridium 187 | OTU205 Christensenellaceae unknown genus 188 | OTU7 Rikenellaceae Blvii28 wastewater-sludge group 189 | OTU36 Family XIV unknown genus 190 | OTU127 Clostridiales Incertae Sedis Proteiniborus 191 | OTU151 Christensenellaceae Christensenellaceae R-7 group 192 | OTU5 Marinilabiaceae Ruminofilibacter 193 | OTU64 Gracilibacteraceae Multi-affiliation 194 | OTU94 Ruminococcaceae Ruminococcus 1 195 | OTU76 unknown family unknown genus 196 | OTU248 Marinilabiaceae Ruminofilibacter 197 | Species 198 | OTU46 unknown species 199 | OTU24 unknown species 200 | OTU68 unknown species 201 | OTU59 Multi-affiliation 202 | OTU28 unknown species 203 | OTU104 Multi-affiliation 204 | OTU61 Multi-affiliation 205 | OTU35 unknown species 206 | OTU118 unknown species 207 | OTU65 unknown species 208 | OTU193 unknown species 209 | OTU54 unknown species 210 | OTU96 unknown species 211 | OTU88 unknown species 212 | OTU43 unknown species 213 | OTU6 unknown species 214 | OTU62 unknown species 215 | OTU56 unknown species 216 | OTU198 Multi-affiliation 217 | OTU144 unknown species 218 | OTU23 unknown species 219 | OTU48 unknown species 220 | OTU135 Multi-affiliation 221 | OTU51 unknown species 222 | OTU74 unknown species 223 | OTU138 unknown species 224 | OTU205 unknown species 225 | OTU7 unknown species 226 | OTU36 unknown species 227 | OTU127 Multi-affiliation 228 | OTU151 unknown species 229 | OTU5 Multi-affiliation 230 | OTU64 Multi-affiliation 231 | OTU94 bacterium enrichment culture clone KWE55-24 232 | OTU76 unknown species 233 | OTU248 Multi-affiliation 234 | 235 | -------------------------------------------------------------------------------- /PLSDAbatch_workflow/GeneratedData/HFHSselected_50_splsda.txt: -------------------------------------------------------------------------------- 1 | $`PLSDA-batch` 2 | HFHS_data$FullData$taxa[x, ] 3 | Kingdom Bacteria 4 | Phylum Firmicutes 5 | Class Clostridia 6 | Order Clostridiales 7 | Family 8 | Genus 9 | Species 10 | 11 | $`Before correction` 12 | Kingdom Phylum Class Order Family 13 | 327808 Bacteria Firmicutes Clostridia Clostridiales Ruminococcaceae 14 | 338796 Bacteria Firmicutes Clostridia Clostridiales Ruminococcaceae 15 | Genus Species 16 | 327808 Oscillospira 17 | 338796 Oscillospira 18 | 19 | $`PLSDA-batch:RUVIII` 20 | HFHS_data$FullData$taxa[x, ] 21 | Kingdom Bacteria 22 | Phylum Firmicutes 23 | Class Clostridia 24 | Order Clostridiales 25 | Family 26 | Genus 27 | Species 28 | 29 | $`ComBat:PLSDA-batch:RUVIII` 30 | Kingdom Phylum Class Order 31 | 186332 Bacteria Firmicutes Clostridia Clostridiales 32 | 262095 Bacteria Firmicutes Erysipelotrichi Erysipelotrichales 33 | 276597 Bacteria Firmicutes Clostridia Clostridiales 34 | Family Genus Species 35 | 186332 Lachnospiraceae [Ruminococcus] gnavus 36 | 262095 Erysipelotrichaceae 37 | 276597 38 | 39 | $`Before correction:removeBatchEffect` 40 | Kingdom Phylum Class Order Family 41 | 581933 Bacteria Firmicutes Clostridia Clostridiales Ruminococcaceae 42 | 206817 Bacteria Bacteroidetes Bacteroidia Bacteroidales S24-7 43 | Genus Species 44 | 581933 Oscillospira 45 | 206817 46 | 47 | $`removeBatchEffect:ComBat:PLSDA-batch` 48 | HFHS_data$FullData$taxa[x, ] 49 | Kingdom Bacteria 50 | Phylum Firmicutes 51 | Class Clostridia 52 | Order Clostridiales 53 | Family Ruminococcaceae 54 | Genus Oscillospira 55 | Species 56 | 57 | $`Before correction:removeBatchEffect:ComBat` 58 | HFHS_data$FullData$taxa[x, ] 59 | Kingdom Bacteria 60 | Phylum Firmicutes 61 | Class Clostridia 62 | Order Clostridiales 63 | Family Ruminococcaceae 64 | Genus Oscillospira 65 | Species 66 | 67 | $`Before correction:removeBatchEffect:RUVIII` 68 | HFHS_data$FullData$taxa[x, ] 69 | Kingdom Bacteria 70 | Phylum Bacteroidetes 71 | Class Bacteroidia 72 | Order Bacteroidales 73 | Family S24-7 74 | Genus 75 | Species 76 | 77 | $`removeBatchEffect:ComBat:PLSDA-batch:RUVIII` 78 | HFHS_data$FullData$taxa[x, ] 79 | Kingdom Bacteria 80 | Phylum Firmicutes 81 | Class Clostridia 82 | Order Clostridiales 83 | Family 84 | Genus 85 | Species 86 | 87 | $`Before correction:removeBatchEffect:ComBat:RUVIII` 88 | HFHS_data$FullData$taxa[x, ] 89 | Kingdom Bacteria 90 | Phylum Bacteroidetes 91 | Class Bacteroidia 92 | Order Bacteroidales 93 | Family S24-7 94 | Genus 95 | Species 96 | 97 | $`Before correction:removeBatchEffect:ComBat:PLSDA-batch` 98 | Kingdom Phylum Class Order Family 99 | 434089 Bacteria Firmicutes Clostridia Clostridiales Ruminococcaceae 100 | 272953 Bacteria Firmicutes Clostridia Clostridiales Ruminococcaceae 101 | 353982 Bacteria Firmicutes Clostridia Clostridiales Ruminococcaceae 102 | 326940 Bacteria Firmicutes Clostridia Clostridiales Ruminococcaceae 103 | Genus Species 104 | 434089 105 | 272953 Oscillospira 106 | 353982 107 | 326940 108 | 109 | $RUVIII 110 | Kingdom Phylum Class Order Family Genus 111 | 398255 Bacteria Bacteroidetes Bacteroidia Bacteroidales S24-7 112 | 205160 Bacteria Bacteroidetes Bacteroidia Bacteroidales S24-7 113 | 384555 Bacteria Bacteroidetes Bacteroidia Bacteroidales S24-7 114 | 1107652 Bacteria Bacteroidetes Bacteroidia Bacteroidales Rikenellaceae 115 | Species 116 | 398255 117 | 205160 118 | 384555 119 | 1107652 120 | 121 | $`Before correction:removeBatchEffect:ComBat:PLSDA-batch:RUVIII` 122 | Kingdom Phylum Class Order 123 | 192222 Bacteria Bacteroidetes Bacteroidia Bacteroidales 124 | 400599 Bacteria Firmicutes Clostridia Clostridiales 125 | 315147 Bacteria Bacteroidetes Bacteroidia Bacteroidales 126 | 348038 Bacteria Bacteroidetes Bacteroidia Bacteroidales 127 | 442846 Bacteria Bacteroidetes Bacteroidia Bacteroidales 128 | 263479 Bacteria Bacteroidetes Bacteroidia Bacteroidales 129 | 175272 Bacteria Bacteroidetes Bacteroidia Bacteroidales 130 | 265322 Bacteria Bacteroidetes Bacteroidia Bacteroidales 131 | 331043 Bacteria Bacteroidetes Bacteroidia Bacteroidales 132 | 339905 Bacteria Bacteroidetes Bacteroidia Bacteroidales 133 | 401384 Bacteria Firmicutes Clostridia Clostridiales 134 | 197644 Bacteria Bacteroidetes Bacteroidia Bacteroidales 135 | 348821 Bacteria Bacteroidetes Bacteroidia Bacteroidales 136 | 198339 Bacteria Bacteroidetes Bacteroidia Bacteroidales 137 | 275218 Bacteria Firmicutes Clostridia Clostridiales 138 | 315430 Bacteria Bacteroidetes Bacteroidia Bacteroidales 139 | 174590 Bacteria Bacteroidetes Bacteroidia Bacteroidales 140 | 184381 Bacteria Bacteroidetes Bacteroidia Bacteroidales 141 | 4378740 Bacteria Bacteroidetes Bacteroidia Bacteroidales 142 | 462764 Bacteria Firmicutes Clostridia Clostridiales 143 | 275476 Bacteria Firmicutes Clostridia Clostridiales 144 | 295564 Bacteria Bacteroidetes Bacteroidia Bacteroidales 145 | 349798 Bacteria Firmicutes Clostridia Clostridiales 146 | 177917 Bacteria Bacteroidetes Bacteroidia Bacteroidales 147 | 177512 Bacteria Bacteroidetes Bacteroidia Bacteroidales 148 | 199118 Bacteria Bacteroidetes Bacteroidia Bacteroidales 149 | 4481506 Bacteria Bacteroidetes Bacteroidia Bacteroidales 150 | 2897325 Bacteria Proteobacteria Deltaproteobacteria Desulfovibrionales 151 | 312440 Bacteria Bacteroidetes Bacteroidia Bacteroidales 152 | 355746 Bacteria Bacteroidetes Bacteroidia Bacteroidales 153 | 196733 Bacteria Bacteroidetes Bacteroidia Bacteroidales 154 | 196672 Bacteria Bacteroidetes Bacteroidia Bacteroidales 155 | 267335 Bacteria Firmicutes Clostridia Clostridiales 156 | 212201 Bacteria Bacteroidetes Bacteroidia Bacteroidales 157 | 272213 Bacteria Firmicutes Clostridia Clostridiales 158 | 1108745 Bacteria Firmicutes Clostridia Clostridiales 159 | 198753 Bacteria Firmicutes Clostridia Clostridiales 160 | 351309 Bacteria Firmicutes Clostridia Clostridiales 161 | 321484 Bacteria Firmicutes Clostridia Clostridiales 162 | Family Genus Species 163 | 192222 Prevotellaceae 164 | 400599 165 | 315147 S24-7 166 | 348038 S24-7 167 | 442846 S24-7 168 | 263479 S24-7 169 | 175272 S24-7 170 | 265322 S24-7 171 | 331043 S24-7 172 | 339905 S24-7 173 | 401384 Ruminococcaceae Oscillospira 174 | 197644 S24-7 175 | 348821 S24-7 176 | 198339 S24-7 177 | 275218 Ruminococcaceae 178 | 315430 S24-7 179 | 174590 S24-7 180 | 184381 S24-7 181 | 4378740 Prevotellaceae Prevotella 182 | 462764 Ruminococcaceae Ruminococcus 183 | 275476 Ruminococcaceae Oscillospira 184 | 295564 S24-7 185 | 349798 Ruminococcaceae Oscillospira 186 | 177917 S24-7 187 | 177512 S24-7 188 | 199118 S24-7 189 | 4481506 S24-7 190 | 2897325 Desulfovibrionaceae Bilophila 191 | 312440 S24-7 192 | 355746 S24-7 193 | 196733 S24-7 194 | 196672 S24-7 195 | 267335 Lachnospiraceae [Ruminococcus] gnavus 196 | 212201 S24-7 197 | 272213 Ruminococcaceae 198 | 1108745 [Mogibacteriaceae] 199 | 198753 Ruminococcaceae 200 | 351309 201 | 321484 Ruminococcaceae Oscillospira 202 | 203 | -------------------------------------------------------------------------------- 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  • PLSDA-batch
  • 7 | after: | 8 |
  • Source codes on github
  • 9 | download: ["pdf", "epub"] 10 | bookdown::pdf_book: 11 | includes: 12 | in_header: preamble.tex 13 | latex_engine: xelatex 14 | citation_package: natbib 15 | keep_tex: yes 16 | toc: yes 17 | toc_depth: 4 18 | bookdown::epub_book: default 19 | -------------------------------------------------------------------------------- /PLSDAbatch_workflow/agis-logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/EvaYiwenWang/PLSDAbatch_workflow/6ed29153e657b109cd232a05a24b9d54a71c59c2/PLSDAbatch_workflow/agis-logo.png -------------------------------------------------------------------------------- /PLSDAbatch_workflow/book.bib: -------------------------------------------------------------------------------- 1 | @article{sacristan2011exploring, 2 | title={Exploring the links between natural products and bacterial assemblages in the sponge Aplysina aerophoba}, 3 | author={Sacrist{\'a}n-Soriano, Oriol and Banaigs, Bernard and Casamayor, Emilio O and Becerro, Mikel A}, 4 | journal={Appl. Environ. Microbiol.}, 5 | volume={77}, 6 | number={3}, 7 | pages={862--870}, 8 | year={2011}, 9 | publisher={Am Soc Microbiol} 10 | } 11 | 12 | 13 | @article{chapleur2016increasing, 14 | title={Increasing concentrations of phenol progressively affect anaerobic digestion of cellulose and associated microbial communities}, 15 | author={Chapleur, Olivier and Madigou, C{\'e}line and Civade, Rapha{\"e}l and Rodolphe, Yohan and Maz{\'e}as, Laurent and Bouchez, Th{\'e}odore}, 16 | journal={Biodegradation}, 17 | volume={27}, 18 | number={1}, 19 | pages={15--27}, 20 | year={2016}, 21 | publisher={Springer} 22 | } 23 | 24 | @article{susin2020variable, 25 | title={Variable selection in microbiome compositional data analysis}, 26 | author={Susin, Antoni and Wang, Yiwen and L{\^e} Cao, Kim-Anh and Calle, M Luz}, 27 | journal={NAR Genomics and Bioinformatics}, 28 | volume={2}, 29 | number={2}, 30 | pages={lqaa029}, 31 | year={2020}, 32 | publisher={Oxford University Press} 33 | } 34 | 35 | 36 | 37 | @article{rohart2017mixomics, 38 | title={mixOmics: An R package for ‘omics feature selection and multiple data integration}, 39 | author={Rohart, Florian and Gautier, Beno{\^\i}t and Singh, Amrit and L{\^e} Cao, Kim-Anh}, 40 | journal={PLoS computational biology}, 41 | volume={13}, 42 | number={11}, 43 | pages={e1005752}, 44 | year={2017}, 45 | publisher={Public Library of Science} 46 | } 47 | 48 | 49 | @article{wang2020multivariate, 50 | title={A multivariate method to correct for batch effects in microbiome data}, 51 | author={Wang, Yiwen and L{\^e} Cao, Kim-Anh}, 52 | journal={bioRxiv}, 53 | year={2020}, 54 | publisher={Cold Spring Harbor Laboratory} 55 | } 56 | 57 | 58 | @article{wang2020characterizing, 59 | title={Characterizing changes in soil microbiome abundance and diversity due to different cover crop techniques}, 60 | author={Wang, Charlotte H and Wu, Linda and Wang, Zengyan and Alabady, Magdy S and Parson, Daniel and Molumo, Zainab and Fankhauser, Sarah C}, 61 | 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\code{batch x treatment designs} from Gaussian distribution 6 | #' using component-based and multivariate strategy. 7 | #' 8 | #' @importFrom Rdpack reprompt 9 | #' @importFrom stats rnorm runif 10 | #' 11 | #' @param mean.batch Numeric, the absolute mean of two batches respectively 12 | #' in batch associated components. 13 | #' @param sd.batch Numeric, the variability (standard deviation) of batch effects. 14 | #' @param mean.trt Numeric, the absolute mean of two treatment groups 15 | #' respectively in treatment associated components. 16 | #' @param sd.trt Numeric, the variability (standard deviation) of 17 | #' treatment effects. 18 | #' @param noise Numeric, the variability (standard deviation) of 19 | #' background noise. 20 | #' @param N Integer, the number of samples. 21 | #' @param p_total Integer, the number of variables. 22 | #' @param p_trt_relevant Integer, the number of variables affected by 23 | #' treatment effects. 24 | #' @param p_bat_relevant Integer, the number of variables affected by 25 | #' batch effects. 26 | #' @param percentage_overlap_samples Numeric, in the range of \eqn{0} 27 | #' to \eqn{1}, the percentage of samples in the first batch and first 28 | #' treatment group. 29 | #' @param percentage_overlap_variables Numeric, in the range of 30 | #' \eqn{0} to \eqn{1}, the percentage of variables with both batch and 31 | #' treatment effects given fixed number of variables with each effect. 32 | #' @param seeds Integer. Default value is randomly selected from 33 | #' \eqn{0} to \eqn{999}. 34 | #' 35 | #' 36 | #' @return \code{simData_Gaussian} returns a list that contains 37 | #' the following components: 38 | #' \item{data}{The simulated data.} 39 | #' \item{cleanData}{The ground-truth data without the batch effect.} 40 | #' \item{Y.trt}{The simulated outcome variable indicating the treatment 41 | #' grouping information.} 42 | #' \item{Y.bat}{The simulated outcome variable indicating the batch 43 | #' grouping information.} 44 | #' \item{true.trt}{The variables assigned with the treatment effect.} 45 | #' \item{true.batch}{The variables assigned with the batch effect.} 46 | #' \item{tComp_relevant}{The component simulated with the treatment effect.} 47 | #' \item{bComp_relevant}{The component simulated with the batch effect.} 48 | #' 49 | #' @author Yiwen Wang, Kim-Anh Lê Cao 50 | #' 51 | #' 52 | #' @references 53 | #' \insertRef{wang2020multivariate}{PLSDAbatch} 54 | #' 55 | #' @examples 56 | #' ## Not run: 57 | #' ## First example 58 | #' ## Balanced batch x treatment design 59 | #' simulation1 <- simData_Gaussian(mean.batch = 7, 60 | #' sd.batch = 8, 61 | #' mean.trt = 3, 62 | #' sd.trt = 2, 63 | #' N = 40, 64 | #' p_total = 300, 65 | #' p_trt_relevant = 60, 66 | #' p_bat_relevant = 150, 67 | #' percentage_overlap_samples = 0.5, 68 | #' percentage_overlap_variables = 0.5, 69 | #' seeds = 1) 70 | #' 71 | #' ## Second example 72 | #' ## Unbalanced batch x treatment design 73 | #' simulation2 <- simData_Gaussian(mean.batch = 7, 74 | #' sd.batch = 8, 75 | #' mean.trt = 3, 76 | #' sd.trt = 2, 77 | #' N = 40, 78 | #' p_total = 300, 79 | #' p_trt_relevant = 60, 80 | #' p_bat_relevant = 150, 81 | #' percentage_overlap_samples = 0.2, 82 | #' percentage_overlap_variables = 0.5, 83 | #' seeds = 1) 84 | #' ## End(Not run) 85 | #' @export 86 | simData_Gaussian = function(mean.batch, 87 | sd.batch = 1, 88 | mean.trt, 89 | sd.trt = 1, 90 | noise = 0.2, 91 | N, 92 | p_total, 93 | p_trt_relevant, 94 | p_bat_relevant, 95 | percentage_overlap_samples = 0.5, 96 | percentage_overlap_variables = 0.5, 97 | seeds = round(runif(1, 0, 999))){ 98 | 99 | set.seed(seeds) 100 | ## 101 | n = N/2 102 | 103 | ### batch component 104 | ## variables for Group 1 105 | bCompG1 <- rnorm(n, mean.batch, sd.batch) 106 | ## variables for Group 2 107 | bCompG2 <- rnorm(n, -mean.batch, sd.batch) 108 | bComp_relevant <- c(bCompG1, bCompG2) 109 | 110 | ### treatment component 111 | ## variables for Group 1 112 | tCompG1 <- rnorm(n, mean.trt, sd.trt) 113 | ## variables for Group 2 114 | tCompG2 <- rnorm(n, -mean.trt, sd.trt) 115 | tComp_relevant <- c(tCompG1[seq_len(n*percentage_overlap_samples)], 116 | tCompG2[seq_len(n*(1-percentage_overlap_samples))], 117 | tCompG1[((n*percentage_overlap_samples)+1):n], 118 | tCompG2[((n*(1-percentage_overlap_samples))+1):n]) 119 | 120 | ## data noise 121 | # background noise is independent 122 | Data.noise <- matrix(rnorm(N*p_total, mean = 0, sd = noise), nrow = N) 123 | 124 | 125 | ### treatment loadings 126 | ## p_trt_relevant variables with trt effects 127 | set.seed(777) # fix loadings for each repeat 128 | w.relevant.t <- sample(c(runif(p_trt_relevant/2,-0.3,-0.2), 129 | runif(p_trt_relevant/2,0.2,0.3))) 130 | w.relevant.t <- w.relevant.t/sqrt(sum(w.relevant.t^2)) 131 | Dat.relevant.t <- matrix(tComp_relevant, ncol = 1) %*% 132 | matrix(w.relevant.t, nrow = 1) 133 | 134 | 135 | ### batch loadings 136 | ## p_bat_relevant variables with batch effects 137 | w.relevant.b <- sample(c(runif(p_bat_relevant/2,-0.3,-0.2), 138 | runif(p_bat_relevant/2,0.2,0.3))) 139 | w.relevant.b <- w.relevant.b/sqrt(sum(w.relevant.b^2)) 140 | Dat.relevant.b <- matrix(bComp_relevant, ncol = 1) %*% 141 | matrix(w.relevant.b, nrow = 1) 142 | 143 | 144 | ## final dataset 145 | ## the index of affected variables with trt effects 146 | index.t <- seq_len(p_trt_relevant) 147 | 148 | ## the largest overlap of variables with both batch and trt effects 149 | overlap.num <- min(p_trt_relevant, p_bat_relevant) 150 | 151 | ## the index of affected variables with batch effects 152 | index.b <- c(sample(index.t, overlap.num*percentage_overlap_variables), 153 | sample((seq_len(p_total))[-index.t], 154 | (p_bat_relevant-overlap.num* 155 | percentage_overlap_variables))) 156 | 157 | finalData <- Data.noise 158 | finalData[,index.t] <- finalData[,index.t] + Dat.relevant.t 159 | finalData[,index.b] <- finalData[,index.b] + Dat.relevant.b 160 | 161 | ## the ground-truth data 162 | cleanData <- Data.noise 163 | cleanData[,index.t] <- cleanData[,index.t] + Dat.relevant.t 164 | 165 | 166 | rownames(finalData) <- rownames(cleanData) <- paste0('sample', seq_len(N)) 167 | 168 | 169 | ## outcome variables 170 | Y.bat <- rep(c("bat1", "bat2"), each = n) 171 | Y.trt <- c(rep("trt1", n*percentage_overlap_samples), 172 | rep("trt2", n*(1-percentage_overlap_samples)), 173 | rep("trt1", n*(1-percentage_overlap_samples)), 174 | rep("trt2", n*percentage_overlap_samples)) 175 | 176 | names(Y.trt) <- names(Y.bat) <- rownames(finalData) 177 | 178 | 179 | return(list(data = finalData, 180 | cleanData = cleanData, 181 | Y.trt = Y.trt, 182 | Y.bat = Y.bat, 183 | true.trt = index.t, 184 | true.batch = index.b, 185 | tComp_relevant = tComp_relevant, 186 | bComp_relevant = bComp_relevant)) 187 | } 188 | 189 | ################################################################################ 190 | #' Data Simulation from Multivariate Negative Binomial Distribution 191 | #' 192 | #' This function simulates data with treatment and batch effects 193 | #' under different \code{batch x treatment designs} from multivariate negative 194 | #' binomial distribution using quantile-quantile transformation between 195 | #' multivariate normal and negative binomial distribution. This function can 196 | #' generate two or three batch groups. 197 | #' 198 | #' 199 | #' @importFrom Rdpack reprompt 200 | #' @importFrom stats rnorm runif model.matrix pnorm qnbinom 201 | #' @importFrom mvtnorm rmvnorm 202 | #' 203 | #' @param batch.group Integer, the number of batch groups. Only valid for 2 or 3 204 | #' batch groups. Default value is 2. 205 | #' @param mean.batch Numeric, the mean of batch effect coefficients for all 206 | #' related variables. 207 | #' @param sd.batch Numeric, the variability (standard deviation) of batch effect 208 | #' coefficients for all related variables. 209 | #' @param mean.trt Numeric, the mean of treatment effect coefficients for all 210 | #' related variables 211 | #' @param sd.trt Numeric, the variability (standard deviation) of treatment 212 | #' effect coefficients for all related variables. 213 | #' @param mean.bg Numeric, the mean of background noise. 214 | #' @param sd.bg Numeric, the variability (standard deviation) of 215 | #' background noise. 216 | #' @param N Integer, the number of samples. 217 | #' @param p_total Integer, the number of variables. 218 | #' @param p_trt_relevant Integer, the number of variables affected by 219 | #' treatment effects. 220 | #' @param p_bat_relevant Integer, the number of variables affected by 221 | #' batch effects. 222 | #' @param percentage_overlap_samples Numeric, in the range of \eqn{0} 223 | #' to \eqn{1}, the percentage of samples from one batch group in one 224 | #' treatment group. 225 | #' @param percentage_overlap_variables Numeric, in the range of \eqn{0} 226 | #' to \eqn{1}, the percentage of variables with both batch and treatment 227 | #' effects given fixed number of variables with each effect. 228 | #' @param data.cor Correlation matrix. The correlation between each pair 229 | #' of variables. 230 | #' @param disp Numeric. The dispersion parameter of negative binomial 231 | #' distribution. 232 | #' @param prob_zero Numeric, in the range of \eqn{0} to \eqn{1}. The probability 233 | #' of each value to be 0. 234 | #' @param seeds Integer. Default value is randomly selected from 235 | #' \eqn{0} to \eqn{999}. 236 | #' 237 | #' 238 | #' 239 | #' @return \code{simData_mnegbinom} returns a list that contains 240 | #' the following components: 241 | #' \item{data}{The simulated data.} 242 | #' \item{cleanData}{The ground-truth data without the batch effect.} 243 | #' \item{data_mu_matrix}{The \eqn{ln} value of the mean to model 244 | #' negative binomial distribution for the simulated data.} 245 | #' \item{clean_mu_matrix}{The \eqn{ln} value of the mean to model 246 | #' negative binomial distribution for the ground-truth data.} 247 | #' \item{Y.trt}{The simulated outcome variable indicating the treatment 248 | #' grouping information.} 249 | #' \item{Y.bat}{The simulated outcome variable indicating the batch 250 | #' grouping information.} 251 | #' \item{true.trt}{The variables assigned with the treatment effect.} 252 | #' \item{true.batch}{The variables assigned with the batch effect.} 253 | #' \item{zero_index}{The indexes of cells containing the resulting counts from 254 | #' the Multivariate Negative Binomial Distribution that are inflated as zero.} 255 | #' 256 | #' @author Yiwen Wang, Kim-Anh Lê Cao 257 | #' 258 | #' 259 | #' @references 260 | #' \insertRef{wang2020multivariate}{PLSDAbatch} 261 | #' 262 | #' @examples 263 | #' ## Not run: 264 | #' ## First example 265 | #' ## To simulate the correlation structure 266 | #' data.cor.res = corStruct(p = 300, zero_prob = 0.7) 267 | #' 268 | #' ## Balanced batch x treatment design 269 | #' simulation <- simData_mnegbinom(mean.batch = 7, 270 | #' sd.batch = 8, 271 | #' mean.trt = 3, 272 | #' sd.trt = 2, 273 | #' mean.bg = 0, 274 | #' sd.bg = 0.2, 275 | #' N = 40, 276 | #' p_total = 300, 277 | #' p_trt_relevant = 100, 278 | #' p_bat_relevant = 200, 279 | #' percentage_overlap_samples = 0.5, 280 | #' percentage_overlap_variables = 0.5, 281 | #' data.cor = data.cor.res$data.cor, 282 | #' disp = 10, 283 | #' prob_zero = 0, 284 | #' seeds = 1) 285 | #' 286 | #' ## Second example 287 | #' ## Unbalanced batch x treatment design 288 | #' simulation <- simData_mnegbinom(mean.batch = 7, 289 | #' sd.batch = 8, 290 | #' mean.trt = 3, 291 | #' sd.trt = 2, 292 | #' mean.bg = 0, 293 | #' sd.bg = 0.2, 294 | #' N = 40, 295 | #' p_total = 300, 296 | #' p_trt_relevant = 100, 297 | #' p_bat_relevant = 200, 298 | #' percentage_overlap_samples = 0.2, 299 | #' percentage_overlap_variables = 0.5, 300 | #' data.cor = data.cor.res$data.cor, 301 | #' disp = 10, 302 | #' prob_zero = 0, 303 | #' seeds = 1) 304 | #' ## End(Not run) 305 | #' 306 | #' @export 307 | simData_mnegbinom = function(batch.group = 2, 308 | mean.batch, 309 | sd.batch = 1, 310 | mean.trt, 311 | sd.trt = 1, 312 | mean.bg = 0, 313 | sd.bg = 0.5, 314 | N, 315 | p_total, 316 | p_trt_relevant, 317 | p_bat_relevant, 318 | percentage_overlap_samples = 0.5, 319 | percentage_overlap_variables = 0.5, 320 | data.cor, 321 | disp = 10, 322 | prob_zero = 0, 323 | seeds = round(runif(1, 0, 999))){ 324 | 325 | set.seed(seeds) 326 | 327 | ## check if the number of batch groups is other than 2 or 3 328 | if(batch.group != 2 & batch.group != 3){ 329 | stop('The number of batch groups has to be 2 or 3.') 330 | } 331 | 332 | if(batch.group == 2){ 333 | # batch info 334 | Y.batch <- rep(c("batch1", "batch2"), each = N/2) 335 | 336 | # treatment info 337 | Y.trt <- c(rep("trt1", (N/2)*percentage_overlap_samples), 338 | rep("trt2", (N/2)*(1-percentage_overlap_samples)), 339 | rep("trt1", (N/2)*(1-percentage_overlap_samples)), 340 | rep("trt2", (N/2)*percentage_overlap_samples)) 341 | } 342 | 343 | if(batch.group == 3){ 344 | # batch info 345 | Y.batch <- rep(c("batch1", "batch2", "batch3"), each = N/3) 346 | 347 | # treatment info 348 | Y.trt <- c(rep("trt1", (N/3)*percentage_overlap_samples), 349 | rep("trt2", (N/3)*(1-percentage_overlap_samples)), 350 | rep("trt1", (N/3)*(1-percentage_overlap_samples)), 351 | rep("trt2", (N/3)*percentage_overlap_samples), 352 | rep("trt1", (N/3)*percentage_overlap_samples), 353 | rep("trt2", (N/3)*(1-percentage_overlap_samples))) 354 | } 355 | 356 | # design matrix 357 | X <- model.matrix(~ as.factor(Y.trt) + as.factor(Y.batch)) 358 | 359 | if(batch.group == 2){ 360 | X <- X[,2:3] # no intercept 361 | 362 | # coefficients matrix 363 | beta = matrix(0, nrow = p_total, ncol = 2) 364 | } 365 | 366 | if(batch.group == 3){ 367 | X <- X[,2:4] # no intercept 368 | 369 | # coefficients matrix 370 | beta = matrix(0, nrow = p_total, ncol = 3) 371 | } 372 | 373 | 374 | # treatment effects related variable coefficients 375 | ## p_trt_relevant variables with trt effects 376 | index.t <- 1:p_trt_relevant 377 | beta[index.t, 1] = rnorm(p_trt_relevant, mean = mean.trt, sd = sd.trt) 378 | 379 | # batch effects related variable coefficients 380 | ## p_bat_relevant variables with batch effects 381 | min.num <- min(p_trt_relevant, p_bat_relevant) 382 | set.seed(777) 383 | index.b <- c(sample(index.t, min.num*percentage_overlap_variables), 384 | sample((1:p_total)[-index.t], 385 | (p_bat_relevant-min.num*percentage_overlap_variables))) 386 | 387 | set.seed(seeds) 388 | if(batch.group == 2){ 389 | beta[index.b, 2] = rnorm(p_bat_relevant, mean = mean.batch, sd = sd.batch) 390 | 391 | # clean data coefficients 392 | beta_clean = beta 393 | beta_clean[, 2] = 0 394 | } 395 | 396 | if(batch.group == 3){ 397 | beta[index.b[1:(p_bat_relevant/2)], 2] = rnorm(p_bat_relevant/2, 398 | mean = mean.batch, 399 | sd = sd.batch) 400 | beta[index.b[(p_bat_relevant/2+1):p_bat_relevant], 401 | 3] = rnorm(p_bat_relevant/2, 402 | mean = mean.batch, 403 | sd = sd.batch) 404 | 405 | # clean data coefficients 406 | beta_clean = beta 407 | beta_clean[, 2:3] = 0 408 | } 409 | 410 | # build mu matrix 411 | ## simu data 412 | mu.simu = X%*%t(beta) 413 | 414 | ## clean data without batch effects 415 | mu.clean = X%*%t(beta_clean) 416 | 417 | # add noise 418 | noise.matrix <- matrix(rnorm(N*p_total, mean = mean.bg, sd = sd.bg), nrow = N) 419 | mu.simu <- mu.simu + noise.matrix 420 | mu.clean <- mu.clean + noise.matrix 421 | 422 | # exponentiation 423 | mu.simu.exp = exp(mu.simu) 424 | mu.clean.exp = exp(mu.clean) 425 | 426 | 427 | gama.simu = rep(disp, N) 428 | normd <- rmvnorm(n = N, mean = rep(0, p_total), sigma = data.cor) 429 | normcdf <- pnorm(normd) 430 | 431 | # simu data 432 | Y <- mapply(normcdf, 433 | mu.simu.exp, 434 | gama.simu, 435 | FUN = function(p, u, gamma){ 436 | qnbinom(p = p, mu = u, size = gamma) 437 | }) 438 | 439 | 440 | # clean data 441 | Y_clean <- mapply(normcdf, 442 | mu.clean.exp, 443 | gama.simu, 444 | FUN = function(p, u, gamma){ 445 | qnbinom(p = p, mu = u, size = gamma) 446 | }) 447 | 448 | # inflate zero 449 | ## simu data 450 | Y_f <- Y 451 | zero_index = runif(length(Y_f)) < prob_zero 452 | Y_f[zero_index] = 0 453 | 454 | ## clean data 455 | Y_clean_f <- Y_clean 456 | Y_clean_f[zero_index] = 0 457 | 458 | Y_f = matrix(Y_f, nrow = N) 459 | Y_clean_f = matrix(Y_clean_f, nrow = N) 460 | 461 | return(list(data = Y_f, 462 | cleanData = Y_clean_f, 463 | data_mu_matrix = mu.simu, 464 | clean_mu_matrix = mu.clean, 465 | Y.trt = Y.trt, 466 | Y.batch = Y.batch, 467 | true.trt = index.t, 468 | true.batch = index.b, 469 | zero_index = zero_index)) 470 | } 471 | 472 | 473 | ################################################################################ 474 | #' Simulation of Correlation Structure for Microbiome Data 475 | #' 476 | #' This function simulates the correlation between variables 477 | #' within the microbiome data. 478 | #' 479 | #' 480 | #' @importFrom Rdpack reprompt 481 | #' @importFrom stats cov2cor runif 482 | #' 483 | #' 484 | #' @param p Integer, the number of variables to simulate. 485 | #' @param zero_prob Numeric, in the range of \eqn{0} to \eqn{1}. The percentage 486 | #' of zeroes in the non-diagonal lower-triangular matrix used to 487 | #' generate the precision matrix. 488 | #' 489 | #' @return \code{corStruct} returns a list that contains 490 | #' the following components: 491 | #' \item{data.cor}{The correlation matrix.} 492 | #' \item{data.precision.m}{The precision matrix, which is the 493 | #' inverse of covariance matrix.} 494 | #' \item{data.cov}{The covariance matrix.} 495 | #' 496 | #' 497 | #' @author Yiwen Wang, Kim-Anh Lê Cao 498 | #' 499 | #' 500 | #' @references 501 | #' \insertRef{mcgregor2020mdine}{PLSDAbatch} 502 | #' 503 | #' @examples 504 | #' data.cor.res = corStruct(p = 300, zero_prob = 0.7) 505 | #' 506 | #' @export 507 | corStruct = function(p, 508 | zero_prob = 0){ 509 | 510 | unif1 <- runif(p*(p-1)/2, min = -1.5, max = 1.5) 511 | unif2 <- runif(p, min = 1.5, max = 2.5) 512 | 513 | # Randomly set lower-triangular elements to zero with probability 'zero_prob'. 514 | unif1_wzero = unif1 515 | unif1_wzero[runif(length(unif1)) < zero_prob] = 0 516 | 517 | data.prec.half <- matrix(0, nrow = p, ncol = p) 518 | data.prec.half[lower.tri(data.prec.half, diag = F)] = unif1_wzero 519 | diag(data.prec.half) <- unif2 520 | 521 | data.prec <- data.prec.half %*% t(data.prec.half) 522 | 523 | data.cov <- solve(data.prec) 524 | 525 | data.cor <- cov2cor(data.cov) 526 | 527 | rownames(data.cor) = colnames(data.cor) = paste0('OTU', 1:p) 528 | 529 | return(list(data.cor = data.cor, 530 | data.precision.m = data.prec, 531 | data.cov = data.cov)) 532 | } 533 | -------------------------------------------------------------------------------- /PLSDAbatch_workflow/data/HD_data.rda: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/EvaYiwenWang/PLSDAbatch_workflow/6ed29153e657b109cd232a05a24b9d54a71c59c2/PLSDAbatch_workflow/data/HD_data.rda -------------------------------------------------------------------------------- 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18 | author = {Yihui Xie}, 19 | year = {2018}, 20 | note = {R package version 1.20}, 21 | url = {https://CRAN.R-project.org/package=knitr}, 22 | } 23 | @Manual{R-rmarkdown, 24 | title = {rmarkdown: Dynamic Documents for R}, 25 | author = {JJ Allaire and Yihui Xie and Jonathan McPherson and Javier Luraschi and Kevin Ushey and Aron Atkins and Hadley Wickham and Joe Cheng and Winston Chang}, 26 | year = {2018}, 27 | note = {R package version 1.10}, 28 | url = {https://CRAN.R-project.org/package=rmarkdown}, 29 | } 30 | -------------------------------------------------------------------------------- /PLSDAbatch_workflow/preamble.tex: -------------------------------------------------------------------------------- 1 | \usepackage{booktabs} 2 | \usepackage{amsthm} 3 | \makeatletter 4 | \def\thm@space@setup{% 5 | \thm@preskip=8pt plus 2pt minus 4pt 6 | \thm@postskip=\thm@preskip 7 | } 8 | \makeatother 9 | 10 | 11 | \usepackage{fancyhdr} 12 | \usepackage{hyperref} 13 | \usepackage{lipsum} 14 | \setlength{\headheight}{28pt} 15 | \setlength{\footskip}{25pt} 16 | \pagestyle{fancy} 17 | \renewcommand{\headrulewidth}{0.5pt} 18 | \renewcommand{\footrulewidth}{0.5pt} 19 | \lhead{\includegraphics[width=8cm,height=1.5cm]{agis-logo}} 20 | \cfoot{\scriptsize Agricultural Genomics Institute at Shenzhen, Chinese Academy 21 | of Agricultural Sciences, China} 22 | \rfoot{\scriptsize \thepage} 23 | \fancyhead[R]{\slshape\leftmark} 24 | \fancypagestyle{plain}{\pagestyle{fancy}} 25 | 26 | \usepackage{fontspec} 27 | \setmainfont{Times New Roman} 28 | -------------------------------------------------------------------------------- /PLSDAbatch_workflow/style.css: -------------------------------------------------------------------------------- 1 | p.caption { 2 | color: #777; 3 | margin-top: 10px; 4 | } 5 | p code { 6 | white-space: inherit; 7 | } 8 | pre { 9 | word-break: normal; 10 | word-wrap: normal; 11 | } 12 | pre code { 13 | white-space: inherit; 14 | } 15 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | This vignette provides all reproducible codes for our article: 3 | 4 | # PLSDA-batch: a multivariate framework to correct for batch effects in microbiome data 5 | 6 | Yiwen Wang, Kim-Anh Lê Cao 7 | 8 | **Abstract:** Microbial communities are highly dynamic and sensitive to changes in the environment. Thus, microbiome data are highly susceptible to batch effects, defined as sources of unwanted variation that are not related to and obscure any factors of interest. Existing batch effect correction methods have been primarily developed for gene expression data. As such, they do not consider the inherent characteristics of microbiome data, including zero inflation, overdispersion and correlation between variables. We introduce new multivariate and non-parametric batch effect correction methods based on Partial Least Squares Discriminant Analysis (PLSDA). PLSDA-batch first estimates treatment and batch variation with latent components, then subtracts batch-associated components from the data. The resulting batch-effect-corrected data can then be input in any downstream statistical analysis. Two variants are proposed to handle unbalanced batch x treatment designs and to avoid overfitting when estimating the components via variable selection. We compare our approaches with popular methods managing batch effects, namely, removeBatchEffect, ComBat and Surrogate Variable Analysis, in simulated and three case studies using various visual and numerical assessments. We show that our three methods lead to competitive performance in removing batch variation while preserving treatment variation, especially for unbalanced batch × treatment designs. Our downstream analyses show selections of biologically relevant taxa. This work demonstrates that batch effect correction methods can improve microbiome research outputs. Reproducible code and vignettes are available on GitHub. 9 | 10 | **Keywords:** microbiome data, multivariate, non-parametric, dimension reduction, batch effect correction 11 | 12 | This article has been published and available as: 13 | 14 | Wang, Y., & Lê Cao, K. A. (2023). PLSDA-batch: a multivariate framework to correct for batch effects in microbiome data. *Briefings in Bioinformatics*, 24(2), bbac622. 15 | 16 | Link: 17 | 18 | We have also implemented a bookdown: 19 | 20 | The R package "PLSDAbatch" can be installed from . 21 | 22 | -------------------------------------------------------------------------------- /docs/PLSDAbatch_workflow.epub: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/EvaYiwenWang/PLSDAbatch_workflow/6ed29153e657b109cd232a05a24b9d54a71c59c2/docs/PLSDAbatch_workflow.epub -------------------------------------------------------------------------------- /docs/PLSDAbatch_workflow.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/EvaYiwenWang/PLSDAbatch_workflow/6ed29153e657b109cd232a05a24b9d54a71c59c2/docs/PLSDAbatch_workflow.pdf 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3 | .hasAnchor:hover a.anchor-section {visibility: visible;} 4 | ul > li > .anchor-section {display: none;} 5 | -------------------------------------------------------------------------------- /docs/libs/anchor-sections-1.1.0/anchor-sections.js: -------------------------------------------------------------------------------- 1 | document.addEventListener('DOMContentLoaded', function () { 2 | // If section divs is used, we need to put the anchor in the child header 3 | const headers = document.querySelectorAll("div.hasAnchor.section[class*='level'] > :first-child") 4 | 5 | headers.forEach(function (x) { 6 | // Add to the header node 7 | if (!x.classList.contains('hasAnchor')) x.classList.add('hasAnchor') 8 | // Remove from the section or div created by Pandoc 9 | x.parentElement.classList.remove('hasAnchor') 10 | }) 11 | }) 12 | -------------------------------------------------------------------------------- /docs/libs/gitbook-2.6.7/css/fontawesome/fontawesome-webfont.ttf: 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25 | top: auto; 26 | } 27 | } 28 | @media (max-width: 600px) { 29 | .book.with-summary .book-header.fixed { 30 | left: calc(100% - 60px); 31 | min-width: 300px; 32 | } 33 | .book.with-summary .book-body { 34 | transform: none; 35 | left: calc(100% - 60px); 36 | min-width: 300px; 37 | } 38 | .book .book-body.fixed { 39 | top: 0; 40 | } 41 | } 42 | 43 | .book .book-body.fixed .body-inner { 44 | top: 50px; 45 | } 46 | .book .book-body .page-wrapper .page-inner section.normal sub, .book .book-body .page-wrapper .page-inner section.normal sup { 47 | font-size: 85%; 48 | } 49 | 50 | @media print { 51 | .book .book-summary, .book .book-body .book-header, .fa { 52 | display: none !important; 53 | } 54 | .book .book-body.fixed { 55 | left: 0px; 56 | } 57 | .book .book-body,.book .book-body .body-inner, .book.with-summary { 58 | overflow: visible !important; 59 | } 60 | } 61 | .kable_wrapper { 62 | border-spacing: 20px 0; 63 | border-collapse: separate; 64 | border: none; 65 | margin: auto; 66 | } 67 | .kable_wrapper > tbody > tr > td { 68 | vertical-align: top; 69 | } 70 | .book .book-body .page-wrapper .page-inner section.normal table tr.header { 71 | border-top-width: 2px; 72 | } 73 | .book .book-body .page-wrapper .page-inner section.normal table tr:last-child td { 74 | border-bottom-width: 2px; 75 | } 76 | .book .book-body .page-wrapper .page-inner section.normal table td, .book .book-body .page-wrapper .page-inner section.normal table th { 77 | border-left: none; 78 | border-right: none; 79 | } 80 | .book .book-body .page-wrapper .page-inner section.normal table.kable_wrapper > tbody > tr, .book .book-body .page-wrapper .page-inner section.normal table.kable_wrapper > tbody > tr > td { 81 | border-top: none; 82 | } 83 | .book .book-body .page-wrapper .page-inner section.normal table.kable_wrapper > tbody > tr:last-child > td { 84 | border-bottom: none; 85 | } 86 | 87 | div.theorem, div.lemma, div.corollary, div.proposition, div.conjecture { 88 | font-style: italic; 89 | } 90 | span.theorem, span.lemma, span.corollary, span.proposition, span.conjecture { 91 | font-style: normal; 92 | } 93 | div.proof>*:last-child:after { 94 | content: "\25a2"; 95 | float: right; 96 | } 97 | .header-section-number { 98 | padding-right: .5em; 99 | } 100 | #header .multi-author { 101 | margin: 0.5em 0 -0.5em 0; 102 | } 103 | #header .date { 104 | margin-top: 1.5em; 105 | } 106 | -------------------------------------------------------------------------------- /docs/libs/gitbook-2.6.7/css/plugin-clipboard.css: -------------------------------------------------------------------------------- 1 | div.sourceCode { 2 | position: relative; 3 | } 4 | 5 | .copy-to-clipboard-button { 6 | position: absolute; 7 | right: 0; 8 | top: 0; 9 | visibility: hidden; 10 | } 11 | 12 | .copy-to-clipboard-button:focus { 13 | outline: 0; 14 | } 15 | 16 | div.sourceCode:hover > .copy-to-clipboard-button { 17 | visibility: visible; 18 | } 19 | -------------------------------------------------------------------------------- /docs/libs/gitbook-2.6.7/css/plugin-fontsettings.css: -------------------------------------------------------------------------------- 1 | /* 2 | * Theme 1 3 | */ 4 | .color-theme-1 .dropdown-menu { 5 | background-color: #111111; 6 | border-color: #7e888b; 7 | } 8 | .color-theme-1 .dropdown-menu .dropdown-caret .caret-inner { 9 | border-bottom: 9px solid #111111; 10 | } 11 | .color-theme-1 .dropdown-menu .buttons { 12 | border-color: #7e888b; 13 | } 14 | .color-theme-1 .dropdown-menu .button { 15 | color: #afa790; 16 | } 17 | .color-theme-1 .dropdown-menu .button:hover { 18 | color: #73553c; 19 | } 20 | /* 21 | * Theme 2 22 | */ 23 | .color-theme-2 .dropdown-menu { 24 | background-color: #2d3143; 25 | border-color: #272a3a; 26 | } 27 | .color-theme-2 .dropdown-menu .dropdown-caret .caret-inner { 28 | border-bottom: 9px solid #2d3143; 29 | } 30 | .color-theme-2 .dropdown-menu .buttons { 31 | border-color: #272a3a; 32 | } 33 | .color-theme-2 .dropdown-menu .button { 34 | color: #62677f; 35 | } 36 | .color-theme-2 .dropdown-menu .button:hover { 37 | color: #f4f4f5; 38 | } 39 | .book .book-header .font-settings .font-enlarge { 40 | line-height: 30px; 41 | font-size: 1.4em; 42 | } 43 | .book .book-header .font-settings .font-reduce { 44 | line-height: 30px; 45 | font-size: 1em; 46 | } 47 | 48 | /* sidebar transition background */ 49 | div.book.color-theme-1 { 50 | background: #f3eacb; 51 | } 52 | .book.color-theme-1 .book-body { 53 | color: #704214; 54 | background: #f3eacb; 55 | } 56 | .book.color-theme-1 .book-body .page-wrapper .page-inner section { 57 | background: #f3eacb; 58 | } 59 | 60 | /* sidebar transition background */ 61 | div.book.color-theme-2 { 62 | background: #1c1f2b; 63 | } 64 | 65 | .book.color-theme-2 .book-body { 66 | color: #bdcadb; 67 | background: #1c1f2b; 68 | } 69 | .book.color-theme-2 .book-body .page-wrapper .page-inner section { 70 | background: #1c1f2b; 71 | } 72 | .book.font-size-0 .book-body .page-inner section { 73 | font-size: 1.2rem; 74 | } 75 | .book.font-size-1 .book-body .page-inner section { 76 | font-size: 1.4rem; 77 | } 78 | .book.font-size-2 .book-body .page-inner section { 79 | font-size: 1.6rem; 80 | } 81 | .book.font-size-3 .book-body .page-inner section { 82 | font-size: 2.2rem; 83 | } 84 | .book.font-size-4 .book-body .page-inner section { 85 | font-size: 4rem; 86 | } 87 | .book.font-family-0 { 88 | font-family: Georgia, serif; 89 | } 90 | .book.font-family-1 { 91 | font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; 92 | } 93 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal { 94 | color: #704214; 95 | } 96 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal a { 97 | color: inherit; 98 | } 99 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal h1, 100 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal h2, 101 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal h3, 102 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal h4, 103 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal h5, 104 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal h6 { 105 | color: inherit; 106 | } 107 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal h1, 108 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal h2 { 109 | border-color: inherit; 110 | } 111 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal h6 { 112 | color: inherit; 113 | } 114 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal hr { 115 | background-color: inherit; 116 | } 117 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal blockquote { 118 | border-color: #c4b29f; 119 | opacity: 0.9; 120 | } 121 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal pre, 122 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal code { 123 | background: #fdf6e3; 124 | color: #657b83; 125 | border-color: #f8df9c; 126 | } 127 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal .highlight { 128 | background-color: inherit; 129 | } 130 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal table th, 131 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal table td { 132 | border-color: #f5d06c; 133 | } 134 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal table tr { 135 | color: inherit; 136 | background-color: #fdf6e3; 137 | border-color: #444444; 138 | } 139 | .book.color-theme-1 .book-body .page-wrapper .page-inner section.normal table tr:nth-child(2n) { 140 | background-color: #fbeecb; 141 | } 142 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal { 143 | color: #bdcadb; 144 | } 145 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal a { 146 | color: #3eb1d0; 147 | } 148 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal h1, 149 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal h2, 150 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal h3, 151 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal h4, 152 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal h5, 153 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal h6 { 154 | color: #fffffa; 155 | } 156 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal h1, 157 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal h2 { 158 | border-color: #373b4e; 159 | } 160 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal h6 { 161 | color: #373b4e; 162 | } 163 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal hr { 164 | background-color: #373b4e; 165 | } 166 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal blockquote { 167 | border-color: #373b4e; 168 | } 169 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal pre, 170 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal code { 171 | color: #9dbed8; 172 | background: #2d3143; 173 | border-color: #2d3143; 174 | } 175 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal .highlight { 176 | background-color: #282a39; 177 | } 178 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal table th, 179 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal table td { 180 | border-color: #3b3f54; 181 | } 182 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal table tr { 183 | color: #b6c2d2; 184 | background-color: #2d3143; 185 | border-color: #3b3f54; 186 | } 187 | .book.color-theme-2 .book-body .page-wrapper .page-inner section.normal table tr:nth-child(2n) { 188 | background-color: #35394b; 189 | } 190 | .book.color-theme-1 .book-header { 191 | color: #afa790; 192 | background: transparent; 193 | } 194 | .book.color-theme-1 .book-header .btn { 195 | color: #afa790; 196 | } 197 | .book.color-theme-1 .book-header .btn:hover { 198 | color: #73553c; 199 | background: none; 200 | } 201 | .book.color-theme-1 .book-header h1 { 202 | color: #704214; 203 | } 204 | .book.color-theme-2 .book-header { 205 | color: #7e888b; 206 | background: transparent; 207 | } 208 | .book.color-theme-2 .book-header .btn { 209 | color: #3b3f54; 210 | } 211 | .book.color-theme-2 .book-header .btn:hover { 212 | color: #fffff5; 213 | background: none; 214 | } 215 | .book.color-theme-2 .book-header h1 { 216 | color: #bdcadb; 217 | } 218 | .book.color-theme-1 .book-body .navigation { 219 | color: #afa790; 220 | } 221 | .book.color-theme-1 .book-body .navigation:hover { 222 | color: #73553c; 223 | } 224 | .book.color-theme-2 .book-body .navigation { 225 | color: #383f52; 226 | } 227 | .book.color-theme-2 .book-body .navigation:hover { 228 | color: #fffff5; 229 | } 230 | /* 231 | * Theme 1 232 | */ 233 | .book.color-theme-1 .book-summary { 234 | color: #afa790; 235 | background: #111111; 236 | border-right: 1px solid rgba(0, 0, 0, 0.07); 237 | } 238 | .book.color-theme-1 .book-summary .book-search { 239 | background: transparent; 240 | } 241 | .book.color-theme-1 .book-summary .book-search input, 242 | .book.color-theme-1 .book-summary .book-search input:focus { 243 | border: 1px solid transparent; 244 | } 245 | .book.color-theme-1 .book-summary ul.summary li.divider { 246 | background: #7e888b; 247 | box-shadow: none; 248 | } 249 | .book.color-theme-1 .book-summary ul.summary li i.fa-check { 250 | color: #33cc33; 251 | } 252 | .book.color-theme-1 .book-summary ul.summary li.done > a { 253 | color: #877f6a; 254 | } 255 | .book.color-theme-1 .book-summary ul.summary li a, 256 | .book.color-theme-1 .book-summary ul.summary li span { 257 | color: #877f6a; 258 | background: transparent; 259 | font-weight: normal; 260 | } 261 | .book.color-theme-1 .book-summary ul.summary li.active > a, 262 | .book.color-theme-1 .book-summary ul.summary li a:hover { 263 | color: #704214; 264 | background: transparent; 265 | font-weight: normal; 266 | } 267 | /* 268 | * Theme 2 269 | */ 270 | .book.color-theme-2 .book-summary { 271 | color: #bcc1d2; 272 | background: #2d3143; 273 | border-right: none; 274 | } 275 | .book.color-theme-2 .book-summary .book-search { 276 | background: transparent; 277 | } 278 | .book.color-theme-2 .book-summary .book-search input, 279 | .book.color-theme-2 .book-summary .book-search input:focus { 280 | border: 1px solid transparent; 281 | } 282 | .book.color-theme-2 .book-summary ul.summary li.divider { 283 | background: #272a3a; 284 | box-shadow: none; 285 | } 286 | .book.color-theme-2 .book-summary ul.summary li i.fa-check { 287 | color: #33cc33; 288 | } 289 | .book.color-theme-2 .book-summary ul.summary li.done > a { 290 | color: #62687f; 291 | } 292 | .book.color-theme-2 .book-summary ul.summary li a, 293 | .book.color-theme-2 .book-summary ul.summary li span { 294 | color: #c1c6d7; 295 | background: transparent; 296 | font-weight: 600; 297 | } 298 | .book.color-theme-2 .book-summary ul.summary li.active > a, 299 | .book.color-theme-2 .book-summary ul.summary li a:hover { 300 | color: #f4f4f5; 301 | background: #252737; 302 | font-weight: 600; 303 | } 304 | -------------------------------------------------------------------------------- /docs/libs/gitbook-2.6.7/css/plugin-search.css: -------------------------------------------------------------------------------- 1 | .book .book-summary .book-search { 2 | padding: 6px; 3 | background: transparent; 4 | position: absolute; 5 | top: -50px; 6 | left: 0px; 7 | right: 0px; 8 | transition: top 0.5s ease; 9 | } 10 | .book .book-summary .book-search input, 11 | .book .book-summary .book-search input:focus, 12 | .book .book-summary .book-search input:hover { 13 | width: 100%; 14 | background: transparent; 15 | border: 1px solid #ccc; 16 | box-shadow: none; 17 | outline: none; 18 | line-height: 22px; 19 | padding: 7px 4px; 20 | color: inherit; 21 | box-sizing: border-box; 22 | } 23 | .book.with-search .book-summary .book-search { 24 | top: 0px; 25 | } 26 | .book.with-search .book-summary ul.summary { 27 | top: 50px; 28 | } 29 | .with-search .summary li[data-level] a[href*=".html#"] { 30 | display: none; 31 | } 32 | -------------------------------------------------------------------------------- /docs/libs/gitbook-2.6.7/css/plugin-table.css: -------------------------------------------------------------------------------- 1 | .book .book-body .page-wrapper .page-inner section.normal table{display:table;width:100%;border-collapse:collapse;border-spacing:0;overflow:auto}.book .book-body .page-wrapper .page-inner section.normal table td,.book .book-body .page-wrapper .page-inner section.normal table th{padding:6px 13px;border:1px solid #ddd}.book .book-body .page-wrapper .page-inner section.normal table tr{background-color:#fff;border-top:1px solid #ccc}.book .book-body .page-wrapper .page-inner section.normal table tr:nth-child(2n){background-color:#f8f8f8}.book .book-body .page-wrapper .page-inner section.normal table th{font-weight:700} 2 | -------------------------------------------------------------------------------- /docs/libs/gitbook-2.6.7/js/clipboard.min.js: -------------------------------------------------------------------------------- 1 | /*! 2 | * clipboard.js v2.0.4 3 | * https://zenorocha.github.io/clipboard.js 4 | * 5 | * Licensed MIT © Zeno Rocha 6 | */ 7 | !function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return function(n){var o={};function r(t){if(o[t])return o[t].exports;var e=o[t]={i:t,l:!1,exports:{}};return n[t].call(e.exports,e,e.exports,r),e.l=!0,e.exports}return r.m=n,r.c=o,r.d=function(t,e,n){r.o(t,e)||Object.defineProperty(t,e,{enumerable:!0,get:n})},r.r=function(t){"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(t,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(t,"__esModule",{value:!0})},r.t=function(e,t){if(1&t&&(e=r(e)),8&t)return e;if(4&t&&"object"==typeof e&&e&&e.__esModule)return e;var n=Object.create(null);if(r.r(n),Object.defineProperty(n,"default",{enumerable:!0,value:e}),2&t&&"string"!=typeof e)for(var o in e)r.d(n,o,function(t){return e[t]}.bind(null,o));return n},r.n=function(t){var e=t&&t.__esModule?function(){return t.default}:function(){return t};return r.d(e,"a",e),e},r.o=function(t,e){return Object.prototype.hasOwnProperty.call(t,e)},r.p="",r(r.s=0)}([function(t,e,n){"use strict";var r="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t},i=function(){function o(t,e){for(var n=0;n indicates arrow keys):', 82 | '/: navigate to previous/next page', 83 | 's: Toggle sidebar']; 84 | if (config.search !== false) info.push('f: Toggle search input ' + 85 | '(use //Enter in the search input to navigate through search matches; ' + 86 | 'press Esc to cancel search)'); 87 | if (config.info !== false) gitbook.toolbar.createButton({ 88 | icon: 'fa fa-info', 89 | label: 'Information about the toolbar', 90 | position: 'left', 91 | onClick: function(e) { 92 | e.preventDefault(); 93 | window.alert(info.join('\n\n')); 94 | } 95 | }); 96 | 97 | // highlight the current section in TOC 98 | var href = window.location.pathname; 99 | href = href.substr(href.lastIndexOf('/') + 1); 100 | // accentuated characters need to be decoded (#819) 101 | href = decodeURIComponent(href); 102 | if (href === '') href = 'index.html'; 103 | var li = $('a[href^="' + href + location.hash + '"]').parent('li.chapter').first(); 104 | var summary = $('ul.summary'), chaps = summary.find('li.chapter'); 105 | if (li.length === 0) li = chaps.first(); 106 | li.addClass('active'); 107 | chaps.on('click', function(e) { 108 | chaps.removeClass('active'); 109 | $(this).addClass('active'); 110 | gs.set('tocScrollTop', summary.scrollTop()); 111 | }); 112 | 113 | var toc = config.toc; 114 | // collapse TOC items that are not for the current chapter 115 | if (toc && toc.collapse) (function() { 116 | var type = toc.collapse; 117 | if (type === 'none') return; 118 | if (type !== 'section' && type !== 'subsection') return; 119 | // sections under chapters 120 | var toc_sub = summary.children('li[data-level]').children('ul'); 121 | if (type === 'section') { 122 | toc_sub.hide() 123 | .parent().has(li).children('ul').show(); 124 | } else { 125 | toc_sub.children('li').children('ul').hide() 126 | .parent().has(li).children('ul').show(); 127 | } 128 | li.children('ul').show(); 129 | var toc_sub2 = toc_sub.children('li'); 130 | if (type === 'section') toc_sub2.children('ul').hide(); 131 | summary.children('li[data-level]').find('a') 132 | .on('click.bookdown', function(e) { 133 | if (href === $(this).attr('href').replace(/#.*/, '')) 134 | $(this).parent('li').children('ul').toggle(); 135 | }); 136 | })(); 137 | 138 | // add tooltips to the 's that are truncated 139 | $('a').each(function(i, el) { 140 | if (el.offsetWidth >= el.scrollWidth) return; 141 | if (typeof el.title === 'undefined') return; 142 | el.title = el.text; 143 | }); 144 | 145 | // restore TOC scroll position 146 | var pos = gs.get('tocScrollTop'); 147 | if (typeof pos !== 'undefined') summary.scrollTop(pos); 148 | 149 | // highlight the TOC item that has same text as the heading in view as scrolling 150 | if (toc && toc.scroll_highlight !== false && li.length > 0) (function() { 151 | // scroll the current TOC item into viewport 152 | var ht = $(window).height(), rect = li[0].getBoundingClientRect(); 153 | if (rect.top >= ht || rect.top <= 0 || rect.bottom <= 0) { 154 | summary.scrollTop(li[0].offsetTop); 155 | } 156 | // current chapter TOC items 157 | var items = $('a[href^="' + href + '"]').parent('li.chapter'), 158 | m = items.length; 159 | if (m === 0) { 160 | items = summary.find('li.chapter'); 161 | m = items.length; 162 | } 163 | if (m === 0) return; 164 | // all section titles on current page 165 | var hs = bookInner.find('.page-inner').find('h1,h2,h3'), n = hs.length, 166 | ts = hs.map(function(i, el) { return $(el).text(); }); 167 | if (n === 0) return; 168 | var scrollHandler = function(e) { 169 | var ht = $(window).height(); 170 | clearTimeout($.data(this, 'scrollTimer')); 171 | $.data(this, 'scrollTimer', setTimeout(function() { 172 | // find the first visible title in the viewport 173 | for (var i = 0; i < n; i++) { 174 | var rect = hs[i].getBoundingClientRect(); 175 | if (rect.top >= 0 && rect.bottom <= ht) break; 176 | } 177 | if (i === n) return; 178 | items.removeClass('active'); 179 | for (var j = 0; j < m; j++) { 180 | if (items.eq(j).children('a').first().text() === ts[i]) break; 181 | } 182 | if (j === m) j = 0; // highlight the chapter title 183 | // search bottom-up for a visible TOC item to highlight; if an item is 184 | // hidden, we check if its parent is visible, and so on 185 | while (j > 0 && items.eq(j).is(':hidden')) j--; 186 | items.eq(j).addClass('active'); 187 | }, 250)); 188 | }; 189 | bookInner.on('scroll.bookdown', scrollHandler); 190 | bookBody.on('scroll.bookdown', scrollHandler); 191 | })(); 192 | 193 | // do not refresh the page if the TOC item points to the current page 194 | $('a[href="' + href + '"]').parent('li.chapter').children('a') 195 | .on('click', function(e) { 196 | bookInner.scrollTop(0); 197 | bookBody.scrollTop(0); 198 | return false; 199 | }); 200 | 201 | var toolbar = config.toolbar; 202 | if (!toolbar || toolbar.position !== 'static') { 203 | var bookHeader = $('.book-header'); 204 | bookBody.addClass('fixed'); 205 | bookHeader.addClass('fixed') 206 | .css('background-color', bookBody.css('background-color')) 207 | .on('click.bookdown', function(e) { 208 | // the theme may have changed after user clicks the theme button 209 | bookHeader.css('background-color', bookBody.css('background-color')); 210 | }); 211 | } 212 | 213 | }); 214 | 215 | gitbook.events.bind("page.change", function(e) { 216 | // store TOC scroll position 217 | var summary = $('ul.summary'); 218 | gs.set('tocScrollTop', summary.scrollTop()); 219 | }); 220 | 221 | var bookBody = $('.book-body'), bookInner = bookBody.find('.body-inner'); 222 | var chapterTitle = function() { 223 | return bookInner.find('.page-inner').find('h1,h2').first().text(); 224 | }; 225 | var saveScrollPos = function(e) { 226 | // save scroll position before page is reloaded 227 | gs.set('bodyScrollTop', { 228 | body: bookBody.scrollTop(), 229 | inner: bookInner.scrollTop(), 230 | focused: document.hasFocus(), 231 | title: chapterTitle() 232 | }); 233 | }; 234 | $(document).on('servr:reload', saveScrollPos); 235 | 236 | // check if the page is loaded in an iframe (e.g. the RStudio preview window) 237 | var inIFrame = function() { 238 | var inIframe = true; 239 | try { inIframe = window.self !== window.top; } catch (e) {} 240 | return inIframe; 241 | }; 242 | if (inIFrame()) { 243 | $(window).on('blur unload', saveScrollPos); 244 | } 245 | 246 | $(function(e) { 247 | var pos = gs.get('bodyScrollTop'); 248 | if (pos) { 249 | if (pos.title === chapterTitle()) { 250 | if (pos.body !== 0) bookBody.scrollTop(pos.body); 251 | if (pos.inner !== 0) bookInner.scrollTop(pos.inner); 252 | } 253 | } 254 | if ((pos && pos.focused) || !inIFrame()) bookInner.find('.page-wrapper').focus(); 255 | // clear book body scroll position 256 | gs.remove('bodyScrollTop'); 257 | }); 258 | 259 | }); 260 | -------------------------------------------------------------------------------- /docs/libs/gitbook-2.6.7/js/plugin-clipboard.js: -------------------------------------------------------------------------------- 1 | gitbook.require(["gitbook", "jQuery"], function(gitbook, $) { 2 | 3 | var copyButton = ''; 4 | var clipboard; 5 | 6 | gitbook.events.bind("page.change", function() { 7 | 8 | if (!ClipboardJS.isSupported()) return; 9 | 10 | // the page.change event is thrown twice: before and after the page changes 11 | if (clipboard) { 12 | // clipboard is already defined but we are on the same page 13 | if (clipboard._prevPage === window.location.pathname) return; 14 | // clipboard is already defined and url path change 15 | // we can deduct that we are before page changes 16 | clipboard.destroy(); // destroy the previous events listeners 17 | clipboard = undefined; // reset the clipboard object 18 | return; 19 | } 20 | 21 | $(copyButton).prependTo("div.sourceCode"); 22 | 23 | clipboard = new ClipboardJS(".copy-to-clipboard-button", { 24 | text: function(trigger) { 25 | return trigger.parentNode.textContent; 26 | } 27 | }); 28 | 29 | clipboard._prevPage = window.location.pathname 30 | 31 | }); 32 | 33 | }); 34 | -------------------------------------------------------------------------------- /docs/libs/gitbook-2.6.7/js/plugin-fontsettings.js: -------------------------------------------------------------------------------- 1 | gitbook.require(["gitbook", "lodash", "jQuery"], function(gitbook, _, $) { 2 | var fontState; 3 | 4 | var THEMES = { 5 | "white": 0, 6 | "sepia": 1, 7 | "night": 2 8 | }; 9 | 10 | var FAMILY = { 11 | "serif": 0, 12 | "sans": 1 13 | }; 14 | 15 | // Save current font settings 16 | function saveFontSettings() { 17 | gitbook.storage.set("fontState", fontState); 18 | update(); 19 | } 20 | 21 | // Increase font size 22 | function enlargeFontSize(e) { 23 | e.preventDefault(); 24 | if (fontState.size >= 4) return; 25 | 26 | fontState.size++; 27 | saveFontSettings(); 28 | }; 29 | 30 | // Decrease font size 31 | function reduceFontSize(e) { 32 | e.preventDefault(); 33 | if (fontState.size <= 0) return; 34 | 35 | fontState.size--; 36 | saveFontSettings(); 37 | }; 38 | 39 | // Change font family 40 | function changeFontFamily(index, e) { 41 | e.preventDefault(); 42 | 43 | fontState.family = index; 44 | saveFontSettings(); 45 | }; 46 | 47 | // Change type of color 48 | function changeColorTheme(index, e) { 49 | e.preventDefault(); 50 | 51 | var $book = $(".book"); 52 | 53 | if (fontState.theme !== 0) 54 | $book.removeClass("color-theme-"+fontState.theme); 55 | 56 | fontState.theme = index; 57 | if (fontState.theme !== 0) 58 | $book.addClass("color-theme-"+fontState.theme); 59 | 60 | saveFontSettings(); 61 | }; 62 | 63 | function update() { 64 | var $book = gitbook.state.$book; 65 | 66 | $(".font-settings .font-family-list li").removeClass("active"); 67 | $(".font-settings .font-family-list li:nth-child("+(fontState.family+1)+")").addClass("active"); 68 | 69 | $book[0].className = $book[0].className.replace(/\bfont-\S+/g, ''); 70 | $book.addClass("font-size-"+fontState.size); 71 | $book.addClass("font-family-"+fontState.family); 72 | 73 | if(fontState.theme !== 0) { 74 | $book[0].className = $book[0].className.replace(/\bcolor-theme-\S+/g, ''); 75 | $book.addClass("color-theme-"+fontState.theme); 76 | } 77 | }; 78 | 79 | function init(config) { 80 | var $bookBody, $book; 81 | 82 | //Find DOM elements. 83 | $book = gitbook.state.$book; 84 | $bookBody = $book.find(".book-body"); 85 | 86 | // Instantiate font state object 87 | fontState = gitbook.storage.get("fontState", { 88 | size: config.size || 2, 89 | family: FAMILY[config.family || "sans"], 90 | theme: THEMES[config.theme || "white"] 91 | }); 92 | 93 | update(); 94 | }; 95 | 96 | 97 | gitbook.events.bind("start", function(e, config) { 98 | var opts = config.fontsettings; 99 | if (!opts) return; 100 | 101 | // Create buttons in toolbar 102 | gitbook.toolbar.createButton({ 103 | icon: 'fa fa-font', 104 | label: 'Font Settings', 105 | className: 'font-settings', 106 | dropdown: [ 107 | [ 108 | { 109 | text: 'A', 110 | className: 'font-reduce', 111 | onClick: reduceFontSize 112 | }, 113 | { 114 | text: 'A', 115 | className: 'font-enlarge', 116 | onClick: enlargeFontSize 117 | } 118 | ], 119 | [ 120 | { 121 | text: 'Serif', 122 | onClick: _.partial(changeFontFamily, 0) 123 | }, 124 | { 125 | text: 'Sans', 126 | onClick: _.partial(changeFontFamily, 1) 127 | } 128 | ], 129 | [ 130 | { 131 | text: 'White', 132 | onClick: _.partial(changeColorTheme, 0) 133 | }, 134 | { 135 | text: 'Sepia', 136 | onClick: _.partial(changeColorTheme, 1) 137 | }, 138 | { 139 | text: 'Night', 140 | onClick: _.partial(changeColorTheme, 2) 141 | } 142 | ] 143 | ] 144 | }); 145 | 146 | 147 | // Init current settings 148 | init(opts); 149 | }); 150 | }); 151 | 152 | 153 | -------------------------------------------------------------------------------- /docs/libs/gitbook-2.6.7/js/plugin-search.js: -------------------------------------------------------------------------------- 1 | gitbook.require(["gitbook", "lodash", "jQuery"], function(gitbook, _, $) { 2 | var index = null; 3 | var fuse = null; 4 | var _search = {engine: 'lunr', opts: {}}; 5 | var $searchInput, $searchLabel, $searchForm; 6 | var $highlighted = [], hi, hiOpts = { className: 'search-highlight' }; 7 | var collapse = false, toc_visible = []; 8 | 9 | function init(config) { 10 | // Instantiate search settings 11 | _search = gitbook.storage.get("search", { 12 | engine: config.search.engine || 'lunr', 13 | opts: config.search.options || {}, 14 | }); 15 | }; 16 | 17 | // Save current search settings 18 | function saveSearchSettings() { 19 | gitbook.storage.set("search", _search); 20 | } 21 | 22 | // Use a specific index 23 | function loadIndex(data) { 24 | // [Yihui] In bookdown, I use a character matrix to store the chapter 25 | // content, and the index is dynamically built on the client side. 26 | // Gitbook prebuilds the index data instead: https://github.com/GitbookIO/plugin-search 27 | // We can certainly do that via R packages V8 and jsonlite, but let's 28 | // see how slow it really is before improving it. On the other hand, 29 | // lunr cannot handle non-English text very well, e.g. the default 30 | // tokenizer cannot deal with Chinese text, so we may want to replace 31 | // lunr with a dumb simple text matching approach. 32 | if (_search.engine === 'lunr') { 33 | index = lunr(function () { 34 | this.ref('url'); 35 | this.field('title', { boost: 10 }); 36 | this.field('body'); 37 | }); 38 | data.map(function(item) { 39 | index.add({ 40 | url: item[0], 41 | title: item[1], 42 | body: item[2] 43 | }); 44 | }); 45 | return; 46 | } 47 | fuse = new Fuse(data.map((_data => { 48 | return { 49 | url: _data[0], 50 | title: _data[1], 51 | body: _data[2] 52 | }; 53 | })), Object.assign( 54 | { 55 | includeScore: true, 56 | threshold: 0.1, 57 | ignoreLocation: true, 58 | keys: ["title", "body"] 59 | }, 60 | _search.opts 61 | )); 62 | } 63 | 64 | // Fetch the search index 65 | function fetchIndex() { 66 | return $.getJSON(gitbook.state.basePath+"/search_index.json") 67 | .then(loadIndex); // [Yihui] we need to use this object later 68 | } 69 | 70 | // Search for a term and return results 71 | function search(q) { 72 | let results = []; 73 | switch (_search.engine) { 74 | case 'fuse': 75 | if (!fuse) return; 76 | results = fuse.search(q).map(function(result) { 77 | var parts = result.item.url.split('#'); 78 | return { 79 | path: parts[0], 80 | hash: parts[1] 81 | }; 82 | }); 83 | break; 84 | case 'lunr': 85 | default: 86 | if (!index) return; 87 | results = _.chain(index.search(q)).map(function(result) { 88 | var parts = result.ref.split("#"); 89 | return { 90 | path: parts[0], 91 | hash: parts[1] 92 | }; 93 | }) 94 | .value(); 95 | } 96 | 97 | // [Yihui] Highlight the search keyword on current page 98 | $highlighted = $('.page-inner') 99 | .unhighlight(hiOpts).highlight(q, hiOpts).find('span.search-highlight'); 100 | scrollToHighlighted(0); 101 | 102 | return results; 103 | } 104 | 105 | // [Yihui] Scroll the chapter body to the i-th highlighted string 106 | function scrollToHighlighted(d) { 107 | var n = $highlighted.length; 108 | hi = hi === undefined ? 0 : hi + d; 109 | // navignate to the previous/next page in the search results if reached the top/bottom 110 | var b = hi < 0; 111 | if (d !== 0 && (b || hi >= n)) { 112 | var path = currentPath(), n2 = toc_visible.length; 113 | if (n2 === 0) return; 114 | for (var i = b ? 0 : n2; (b && i < n2) || (!b && i >= 0); i += b ? 1 : -1) { 115 | if (toc_visible.eq(i).data('path') === path) break; 116 | } 117 | i += b ? -1 : 1; 118 | if (i < 0) i = n2 - 1; 119 | if (i >= n2) i = 0; 120 | var lnk = toc_visible.eq(i).find('a[href$=".html"]'); 121 | if (lnk.length) lnk[0].click(); 122 | return; 123 | } 124 | if (n === 0) return; 125 | var $p = $highlighted.eq(hi); 126 | $p[0].scrollIntoView(); 127 | $highlighted.css('background-color', ''); 128 | // an orange background color on the current item and removed later 129 | $p.css('background-color', 'orange'); 130 | setTimeout(function() { 131 | $p.css('background-color', ''); 132 | }, 2000); 133 | } 134 | 135 | function currentPath() { 136 | var href = window.location.pathname; 137 | href = href.substr(href.lastIndexOf('/') + 1); 138 | return href === '' ? 'index.html' : href; 139 | } 140 | 141 | // Create search form 142 | function createForm(value) { 143 | if ($searchForm) $searchForm.remove(); 144 | if ($searchLabel) $searchLabel.remove(); 145 | if ($searchInput) $searchInput.remove(); 146 | 147 | $searchForm = $('
    ', { 148 | 'class': 'book-search', 149 | 'role': 'search' 150 | }); 151 | 152 | $searchLabel = $('