├── manuscript ├── gtdb_hmmsearch_for_loop_bash.sh ├── data analysis │ ├── remove_duplicate_genes.py │ ├── parse_diamond_argument.py │ ├── cutoff_score.csv │ ├── .ipynb_checkpoints │ │ └── cutoff_score-checkpoint.csv │ ├── filter_hmm_scores_aboveTC.py │ └── filter_hmm_scores_TC_NC_exploration.py ├── summarize_hmm_results_gtdb.pl ├── HMM build.md ├── .ipynb_checkpoints │ ├── HMM build-checkpoint.md │ └── Database creation-checkpoint.md ├── plotting │ ├── isolate_genomes_plot.R │ ├── allMGs_above_0.8.R │ └── GTDB_summary_table_data_manipulation.r ├── normalize_hmm_scores_taxonomy_and_metadata.py └── Database creation.md ├── README.md ├── .ipynb_checkpoints ├── README-checkpoint.md └── License-checkpoint ├── License └── HMMs └── individual HMMs ├── TmoB_BmoB.hmm └── TomA4.hmm /manuscript/gtdb_hmmsearch_for_loop_bash.sh: -------------------------------------------------------------------------------- 1 | #runs hmmsearch on all genomes within a folder (containing downloaded GTDB genomes). Creates tbl file for each result 2 | 3 | for Genome in ./protein_faa_reps/done_v1/*_protein.faa 4 | do 5 | base=$(basename $Genome _protein.faa) 6 | echo $base 7 | hmmsearch --cpu 10 --notextw --tblout ./TblOuts/${base}.tbl CANT-HYD.hmm ./protein_faa_reps/done_v1/${base}_protein.faa >/dev/null 2>&1 8 | done 9 | -------------------------------------------------------------------------------- /manuscript/data analysis/remove_duplicate_genes.py: -------------------------------------------------------------------------------- 1 | #! usr/pyenv/python3 2 | 3 | import pandas as pd 4 | from pandas import DataFrame 5 | 6 | import csv, sys, re 7 | 8 | infile=sys.argv[1] 9 | outfile=sys.argv[2] 10 | 11 | df=pd.read_csv(infile,sep='\t') 12 | df['Domain_Score']=pd.to_numeric(df['Domain_Score'],errors='coerce') 13 | df_sorted=df.sort_values(['Query', 'Domain_Score'], ascending=[True, False]) 14 | df_drop_dup=df_sorted.drop_duplicates(subset=['Query'],keep='first') 15 | 16 | df_drop_dup.to_csv(outfile,sep='\t',header=True,index=False) 17 | -------------------------------------------------------------------------------- /manuscript/summarize_hmm_results_gtdb.pl: -------------------------------------------------------------------------------- 1 | #!/usr/bin/perl 2 | 3 | #this script summarizes all individual GTDB HMM results from gtdb_hmmsearch_for_loop_bash.sh into one table containing accessions, scores, and e-values 4 | 5 | use strict; 6 | 7 | #USAGE: $0 8 | my $Dir = $ARGV[0]; 9 | opendir(DIR,$Dir) or die "Can't open the folder"; 10 | my @files = readdir(DIR); 11 | print "GTDB_Acc\tHMM\tEvalue\tScore\tAccession\n"; 12 | foreach my $f (@files){ 13 | my $genome = $f; 14 | $genome =~ s/\.tbl//; 15 | open(FH,"./$Dir/$f") or die "Can't open the file: $f"; 16 | while(my $line = ){ 17 | if($line =~/^#/){ } 18 | else{ 19 | $line =~ tr/ +/ /s; 20 | my @data = split(/ /,$line); 21 | print "$genome\t$data[2]\t$data[7]\t$data[8]\t$data[0]\n"; 22 | } 23 | } 24 | } 25 | -------------------------------------------------------------------------------- /manuscript/HMM build.md: -------------------------------------------------------------------------------- 1 | # **HMM build commands** 2 | 3 | 1. Extract clustered sequences using the accessions identified from the phylogentic tree analysis 4 | 5 | ```bash 6 | grep -w -Ff HMM_accession_lists/Group31_con1_apcE_EXP_accesion.UNIX.list Test/cluster/Group31.uniques.clusters.uc | awk '{print $9}' | sort -u | grep -A 1 --no-group-separator -f /dev/stdin Test/Group31.uniques.singleline.fasta > HMM/Group31.fasta 7 | ``` 8 | 9 | 2. Extract and add reference sequences 10 | 11 | ```bash 12 | grep -w -Ff Group3_con2_AlkylSuccinateSynthaseSubunitD_accession.UNIX.list ../Alignment/All_hydrocarbon_reference_sequences_singleline.fasta -A 1 --no-group-separator >> ../HMM/Group3_con2_AlkylSuccinateSynthaseSubunitD.fasta 13 | ``` 14 | 15 | 3. Align sequences using [Clustal Omega](https://www.ebi.ac.uk/Tools/msa/clustalo/) web service, with default parameters 16 | 17 | 4. Build HMM for each target degradation gene using [HMMER](http://hmmer.org/) 18 | 19 | ```bash 20 | hmmbuild -n HMM/Group31 --amino --informat afa HMM/Group31.hmm HMM/Group31.align.fasta 21 | ``` -------------------------------------------------------------------------------- /manuscript/.ipynb_checkpoints/HMM build-checkpoint.md: -------------------------------------------------------------------------------- 1 | # **HMM build commands** 2 | 3 | 1. Extract clustered sequences using the accessions identified from the phylogentic tree analysis 4 | 5 | ```bash 6 | grep -w -Ff HMM_accession_lists/Group31_con1_apcE_EXP_accesion.UNIX.list Test/cluster/Group31.uniques.clusters.uc | awk '{print $9}' | sort -u | grep -A 1 --no-group-separator -f /dev/stdin Test/Group31.uniques.singleline.fasta > HMM/Group31.fasta 7 | ``` 8 | 9 | 2. Extract and add reference sequences 10 | 11 | ```bash 12 | grep -w -Ff Group3_con2_AlkylSuccinateSynthaseSubunitD_accession.UNIX.list ../Alignment/All_hydrocarbon_reference_sequences_singleline.fasta -A 1 --no-group-separator >> ../HMM/Group3_con2_AlkylSuccinateSynthaseSubunitD.fasta 13 | ``` 14 | 15 | 3. Align sequences using [Clustal Omega](https://www.ebi.ac.uk/Tools/msa/clustalo/) web service, with default parameters 16 | 17 | 4. Build HMM for each target degradation gene using [HMMER](http://hmmer.org/) 18 | 19 | ```bash 20 | hmmbuild -n HMM/Group31 --amino --informat afa HMM/Group31.hmm HMM/Group31.align.fasta 21 | ``` -------------------------------------------------------------------------------- /manuscript/data analysis/parse_diamond_argument.py: -------------------------------------------------------------------------------- 1 | #! usr/pyenv/python3 2 | 3 | import glob,re,os,sys 4 | from pathlib import Path 5 | 6 | blast_file="/gpfs/ebg_work/hackathon/diamond/diamondout_All_hydrocarbon_reference_sequences.txt" 7 | 8 | def make_fasta(f_path,out): 9 | with open(f_path,'r') as group,open(blast_file,'r') as blast, open(out, 'a') as fasta: 10 | seqid=[] 11 | 12 | for line in group: 13 | line=line.strip('\n') 14 | seqid.append(line) 15 | print(seqid) 16 | 17 | for line in blast: 18 | cols=line.split('\t') 19 | #print(cols) 20 | if cols[0] in seqid: 21 | print(cols[0]) 22 | fasta.write('>' + cols[1] + '\n' + cols[12] + '\n') 23 | return; 24 | 25 | def main(): 26 | import re 27 | directory=sys.argv[1] 28 | groups=[] 29 | for file in os.listdir(directory): 30 | if file.startswith("Homolog"): 31 | groups.append(file) 32 | print(groups) 33 | 34 | for f in groups: 35 | print(f) 36 | g_num=int(''.join(filter(str.isdigit,f))) 37 | fpath=f"{directory}/{f}" 38 | out=f"{directory}/Group{g_num}.faa" 39 | make_fasta(fpath,out) 40 | main() 41 | 42 | 43 | 44 | 45 | 46 | -------------------------------------------------------------------------------- /manuscript/data analysis/cutoff_score.csv: -------------------------------------------------------------------------------- 1 | PrmA,1000,890,alkane,aerobic 2 | PrmC,800,630,alkane,aerobic 3 | TmoB_BmoB,180,140,aromatic,aerobic 4 | TmoA_BmoA,900,810,aromatic,aerobic 5 | TmoE,500,350,aromatic,aerobic 6 | TomA1,660,600,aromatic,aerobic 7 | TomA3,1040,960,aromatic,aerobic 8 | AssA,1160,800,alkane,anaerobic 9 | BssA,1600,1150,aromatic,anaerobic 10 | NmsA,1550,1200,aromatic,anaerobic 11 | MAH_beta,220,170,aromatic,aerobic 12 | PAH_NdoC,200,180,aromatic,aerobic 13 | EbdA,1700,900,aromatic,anaerobic 14 | CmdA,1000,620,aromatic,anaerobic 15 | ahyA,710,490,alkane,anaerobic 16 | AlkB,550,530,alkane,aerobic 17 | dszC,560,400,aromatic,aerobic 18 | pBmoC,300,190,alkane,aerobic 19 | pBmoA,400,270,alkane,aerobic 20 | pBmoB,350,250,alkane,aerobic 21 | sBmoZ,250,150,alkane,aerobic 22 | AbcA_1,1200,600,aromatic,anaerobic 23 | AbcA_2,1000,900,aromatic,anaerobic 24 | K27540,900,670,aromatic,anaerobic 25 | sBmoX,1050,850,alkane,aerobic 26 | sBmoY,800,500,alkane,aerobic 27 | CYP153,590,480,alkane,aerobic 28 | MAH_alpha,630,470,aromatic,aerobic 29 | NdoB,630,370,aromatic,aerobic 30 | non_NdoB_type,430,400,aromatic,aerobic 31 | almA_GroupI,900,830,alkane,aerobic 32 | almA_GroupIII,900,830,alkane,aerobic 33 | LadA_alpha,590,500,alkane,aerobic 34 | LadA_beta,740,670,alkane,aerobic 35 | LadB,500,350,alkane,aerobic 36 | DmpO,180,130,aromatic,aerobic 37 | TomA4,200,150,aromatic,aerobic 38 | -------------------------------------------------------------------------------- /manuscript/data analysis/.ipynb_checkpoints/cutoff_score-checkpoint.csv: -------------------------------------------------------------------------------- 1 | PrmA,1000,890,alkane,aerobic 2 | PrmC,800,630,alkane,aerobic 3 | TmoB_BmoB,180,140,aromatic,aerobic 4 | TmoA_BmoA,900,810,aromatic,aerobic 5 | TmoE,500,350,aromatic,aerobic 6 | TomA1,660,600,aromatic,aerobic 7 | TomA3,1040,960,aromatic,aerobic 8 | AssA,1160,800,alkane,anaerobic 9 | BssA,1600,1150,aromatic,anaerobic 10 | NmsA,1550,1200,aromatic,anaerobic 11 | MAH_beta,220,170,aromatic,aerobic 12 | PAH_NdoC,200,180,aromatic,aerobic 13 | EbdA,1700,900,aromatic,anaerobic 14 | CmdA,1000,620,aromatic,anaerobic 15 | ahyA,710,490,alkane,anaerobic 16 | AlkB,550,530,alkane,aerobic 17 | dszC,560,400,aromatic,aerobic 18 | pBmoC,300,190,alkane,aerobic 19 | pBmoA,400,270,alkane,aerobic 20 | pBmoB,350,250,alkane,aerobic 21 | sBmoZ,250,150,alkane,aerobic 22 | AbcA_1,1200,600,aromatic,anaerobic 23 | AbcA_2,1000,900,aromatic,anaerobic 24 | K27540,900,670,aromatic,anaerobic 25 | sBmoX,1050,850,alkane,aerobic 26 | sBmoY,800,500,alkane,aerobic 27 | CYP153,590,480,alkane,aerobic 28 | MAH_alpha,630,470,aromatic,aerobic 29 | NdoB,630,370,aromatic,aerobic 30 | non_NdoB_type,430,400,aromatic,aerobic 31 | almA_GroupI,900,830,alkane,aerobic 32 | almA_GroupIII,900,830,alkane,aerobic 33 | LadA_alpha,590,500,alkane,aerobic 34 | LadA_beta,740,670,alkane,aerobic 35 | LadB,500,350,alkane,aerobic 36 | DmpO,180,130,aromatic,aerobic 37 | TomA4,200,150,aromatic,aerobic 38 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # CANT-HYD: a curated database of phylogeny-derived hidden markov models for annotation of marker genes involved in hydrocarbon degradation 2 | 3 | The **C**algary approach to **AN**no**T**ating **HYD**rocarbon degrading enzymes is a database used for robust and accurate annotation of genes associated with aerobic and anaerobic hydrocarbon degradation. 4 | 5 | ## Implementation 6 | 7 | 1. Download [individual](https://github.com/dgittins/CANT-HYD-HydrocarbonBiodegradation/blob/main/HMMs/individual%20HMMs) or [concatenated](https://github.com/dgittins/CANT-HYD-HydrocarbonBiodegradation/tree/main/HMMs/concatenated%20HMMs) HMM files from this GitHub repository 8 | 9 | 2. Annotate protein-coding gene predictions from microbial whole genomes and metagenome-assembled genomes using CANT-HYD HMMs implemented in [HMMER](http://hmmer.org/) 10 | 11 | ```bash 12 | hmmsearch --tblout hmmsearch_metagenome.tblout CANT-HYD.hmm metagenome_proteins.faa > hmmsearch_metagenome.out 13 | ``` 14 | 15 |          Options: 16 | 17 |          a. ```--cut_tc``` for trusted cutoff 18 | 19 |          b. ```--cut_nc``` for noise cutoff 20 | 21 |          c. no option, for exploring genes below the noise cutoff 22 | 23 | 24 | ## Article 25 | 26 | Khot V, Zorz J, Gittins DA, Chakraborty A, Bell E, Bautista MA, Paquette AJ, Hawley AK, Novotnik B, Hubert CRJ, Strous M and Bhatnagar S (2022) **CANT-HYD: A Curated Database of Phylogeny-Derived Hidden Markov Models for Annotation of Marker Genes Involved in Hydrocarbon Degradation.** *Front. Microbiol.* 12:764058. doi: [10.3389/fmicb.2021.764058](https://www.frontiersin.org/articles/10.3389/fmicb.2021.764058/full) 27 | -------------------------------------------------------------------------------- /.ipynb_checkpoints/README-checkpoint.md: -------------------------------------------------------------------------------- 1 | # CANT-HYD: A database and algorithm for accurate annotation of hydrocarbon degradation genes 2 | 3 | The **C**algary approach to **AN**no**T**ating **HYD**rocarbon degrading enzymes is a database used for robust and accurate annotation of genes associated with aerobic and anaerobic hydrocarbon degradation. 4 | 5 | ## Implementation 6 | 7 | 1. Download [CANT_HYD.hmm](https://github.com/dgittins/CANT-HYD-HydrocarbonBiodegradation/blob/main/downloads/CANT_HYD.hmm), [HMM_confidence_score.csv](https://github.com/dgittins/CANT-HYD-HydrocarbonBiodegradation/blob/main/downloads/HMM_confidence_score.csv), and [parse_hmmsearch_output.py](https://github.com/dgittins/CANT-HYD-HydrocarbonBiodegradation/blob/main/downloads/parse_hmmsearch_output.py) files from this GitHub repository 8 | 9 | 2. Annotate protein-coding gene predictions from microbial whole genomes and metagenome-assembled genomes using CANT-HYD HMMs implemented in [HMMER](http://hmmer.org/) 10 | 11 | ```bash 12 | hmmsearch --tblout hmmsearch_metagenome.tblout CANT-HYD.hmm metagenome_proteins.faa > hmmsearch_metagenome.out 13 | ``` 14 | 15 | 3. Filter HMM search ouput to sequence homologs above the confidence threshold 16 | 17 | ```bash 18 | python parse_hmm_output.py HMM_confidence_score.csv hmmsearch_metagenome.tblout hmmsearch_metagenome.parse.txt 19 | ``` 20 | 21 | ## Contributors 22 | 23 | Varada Khot2, Jackie Zorz2, Daniel Gittins1 24 | 25 | Anirban Chakraborty1, Emma Bell1, Maria A. Bautista1, Alexandre Paquette2, Casey Hubert1, Marc Strous2 26 | 27 | Srijak Bhatnagar1 28 | 29 | 1Department of Biological Sciences, University of Calgary, Calgary 30 | Alberta 31 | 32 | 2Department of Geoscience, University of Calgary, Calgary Alberta 33 | -------------------------------------------------------------------------------- /manuscript/plotting/isolate_genomes_plot.R: -------------------------------------------------------------------------------- 1 | library(reshape2) 2 | library(dplyr) 3 | library(tidyr) 4 | library(ggplot2) 5 | 6 | setwd("alkanes_hackathon/validation/") 7 | 8 | f <- read.table("./isolate_hmmsearch_results.csv", header=TRUE,sep="\t") 9 | 10 | f_m <- melt(f,id=c("genome","genome_class")) 11 | 12 | write.csv(f_m,"isolate_hmmsearch_results_long.csv") 13 | f_m_new <- read.csv("isolate_hmmsearch_results_long.csv") 14 | 15 | f_m_new$genome <- factor(f_m_new$genome,levels = unique(f_m_new$genome)) 16 | 17 | p1 <- ggplot(f_m_new,aes(x=genome,y=hmm_new_name))+ 18 | geom_point(aes(size = value,colour=hmm_class),alpha=0.75)+ 19 | facet_grid(hmm_class ~genome_class,scales = "free", space = "free",labeller = label_wrap_gen())+ 20 | scale_size_continuous(limits=c(1,9),range = c(1.5,9),breaks=c(1,3,5,7))+ 21 | labs(size="Count of Normalized Scores > 1",colour="HMM Classification")+ 22 | theme(axis.text.y=element_text(colour="#31393C",size=10), 23 | axis.ticks.y=element_blank(), 24 | axis.title=element_blank(), 25 | axis.text.x=element_blank(),#text(angle=90,hjust=1,vjust=0.3, colour="#31393C",size=12), 26 | legend.title = element_text(size = 11), panel.background = element_blank(), 27 | legend.text = element_text(size=11,color = "#31393C"), 28 | panel.border = element_rect(colour = "#e6e6e6ff", fill = NA, size = 1.2), 29 | legend.position = "right", 30 | panel.grid.major.y = element_line(colour = "#fafafaff"), 31 | panel.grid.major.x = element_line(colour="#fafafaff"), 32 | strip.text.x = element_text(colour="black",size=10,angle=90), 33 | strip.text.y = element_text(colour="black",size=10,angle=0), 34 | strip.background = element_rect(fill = "#f2f2f2ff",color = "#fafafaff"))+ 35 | scale_color_manual(values = c("#3381FF","#ADDAFF","#EC8609","#FED872"), guide = guide_legend(override.aes = list(size=5)))# 36 | p1 37 | 38 | -------------------------------------------------------------------------------- /manuscript/data analysis/filter_hmm_scores_aboveTC.py: -------------------------------------------------------------------------------- 1 | #!usr/pyenv/python3 2 | #this script is for VALIDATION - will filter everything above TRUSTED CUTOFF and appends the oxygen use and HC_type (aerobic aromatic etc) 3 | 4 | import sys, csv, argparse, itertools 5 | #cutoff_file=sys.argv[1] #comma seperated file of HMM name and max possible scores and degradation types 6 | #hmm_file=sys.argv[2] #HMM search table output 7 | #out_file=sys.argv[3] #output file 8 | 9 | 10 | parser=argparse.ArgumentParser(description='This script normalizes domain scores for hmmsearch results to the HC_degradation hmm database') 11 | 12 | 13 | parser.add_argument('-c','--csv',help='csv file of max possible scores and degradation types') 14 | parser.add_argument('-t','--tbl',help='tblout file from hmmsearch') 15 | parser.add_argument('-o','--output',help='output file for normalized results') 16 | 17 | args=parser.parse_args() 18 | cutoff_file=args.csv 19 | hmm_file=args.tbl 20 | out_file=args.output 21 | 22 | max_score={} 23 | 24 | with open(cutoff_file, 'r') as score: 25 | for line in score: 26 | col=line.strip().split(',') 27 | max_score[col[0]]=[col[1],col[2],col[3],col[4]] #adds hmm name as key and Trusted and noise cutoffs and degradation type as values (Group13_con1_AC_PrmA: [1000,890,aerobic,aromatic]) 28 | #print(max_score) 29 | 30 | with open (hmm_file, 'r') as hmm, open (out_file, 'a', newline= '') as out: 31 | linewriter=csv.writer(out, delimiter ='\t')#,quoting=csv.QUOTE_NONE, quotechar='',escapechar='') 32 | linewriter.writerow(["Query","-","HMM","-","E-value","Score","Bias","Domain_E-value","Domain_Score","Domain_Bias","Oxygen_Use","HC_Type"]) 33 | for line in hmm: 34 | if not line.startswith('#'): 35 | cols = line.strip('\n').split() #splits on whitespace 36 | # print(cols) 37 | line_new='\t'.join(cols[0:10]) 38 | # print(line_new) 39 | if cols[2] in max_score.keys(): 40 | if float(cols[8]) >= float(max_score[cols[2]][0]): #if the domain score is greater than the trusted cutoff (for validation) 41 | metabol=max_score[cols[2]][2] 42 | HC_type=max_score[cols[2]][3] 43 | # linewriter.writerow([line_new,str(round(nor_score,3)),metabol,HC_type]) 44 | out.write(line_new + '\t' + metabol +'\t' + HC_type+ '\n') #writes line and normalized score and degradation type at the end 45 | continue 46 | print("Finished normalizing " + hmm_file) 47 | -------------------------------------------------------------------------------- /manuscript/data analysis/filter_hmm_scores_TC_NC_exploration.py: -------------------------------------------------------------------------------- 1 | #!usr/pyenv/python3 2 | #this script is for EXPLORATION - will filter everything above NOISE CUTOFF and appends the oxygen use and HC_type (aerobic aromatic etc) 3 | 4 | import sys, csv, argparse, itertools 5 | #cutoff_file=sys.argv[1] #comma seperated file of HMM name and max possible scores and degradation types 6 | #hmm_file=sys.argv[2] #HMM search table output 7 | #out_file=sys.argv[3] #output file 8 | 9 | 10 | parser=argparse.ArgumentParser(description='This script normalizes domain scores for hmmsearch results to the HC_degradation hmm database') 11 | 12 | 13 | parser.add_argument('-c','--csv',help='csv file of max possible scores and degradation types') 14 | parser.add_argument('-t','--tbl',help='tblout file from hmmsearch') 15 | parser.add_argument('-o','--output',help='output file for normalized results') 16 | 17 | args=parser.parse_args() 18 | cutoff_file=args.csv 19 | hmm_file=args.tbl 20 | out_file=args.output 21 | 22 | max_score={} 23 | 24 | with open(cutoff_file, 'r') as score: 25 | for line in score: 26 | col=line.strip().split(',') 27 | max_score[col[0]]=[col[1],col[2],col[3],col[4]] #adds hmm name as key and Trusted and noise cutoffs and degradation type as values (Group13_con1_AC_PrmA: [1000,890,aerobic,aromatic]) 28 | #print(max_score) 29 | 30 | with open (hmm_file, 'r') as hmm, open (out_file, 'a', newline= '') as out: 31 | linewriter=csv.writer(out, delimiter ='\t')#,quoting=csv.QUOTE_NONE, quotechar='',escapechar='') 32 | linewriter.writerow(["Query","-","HMM","-","E-value","Score","Bias","Domain_E-value","Domain_Score","Domain_Bias","Oxygen_Use","HC_Type"]) 33 | for line in hmm: 34 | if not line.startswith('#'): 35 | cols = line.strip('\n').split() #splits on whitespace 36 | # print(cols) 37 | line_new='\t'.join(cols[0:10]) 38 | # print(line_new) 39 | if cols[2] in max_score.keys(): 40 | if float(cols[8]) >= float(max_score[cols[2]][1]): #if the domain score is greater than the noise cutoff (for exploration) 41 | metabol=max_score[cols[2]][2] 42 | HC_type=max_score[cols[2]][3] 43 | # linewriter.writerow([line_new,str(round(nor_score,3)),metabol,HC_type]) 44 | out.write(line_new + '\t' + metabol +'\t' + HC_type+ '\n') #writes line and normalized score and degradation type at the end 45 | continue 46 | print("Finished normalizing " + hmm_file) 47 | -------------------------------------------------------------------------------- /manuscript/normalize_hmm_scores_taxonomy_and_metadata.py: -------------------------------------------------------------------------------- 1 | #! usr/pyenv/python3 2 | #script normalizes the domain score by its max possible hit score and appends the normalized score (between 0-1) and also the oxygen use and HC_type (aerobic aromatic etc) to the summary table 3 | 4 | import sys, csv, argparse 5 | #cutoff_file=sys.argv[1] #comma seperated file of HMM name and max possible scores and degradation types 6 | #hmm_file=sys.argv[2] #HMM search summary table output (from summarize_hmm_results_gtdb.pl script) 7 | #out_file=sys.argv[3] #output file 8 | 9 | 10 | parser=argparse.ArgumentParser(description='This script normalizes domain scores for hmmsearch results to the HC_degradation hmm database') 11 | 12 | 13 | parser.add_argument('-c','--csv',help='csv file of max possible scores and degradation types') 14 | parser.add_argument('-t','--tbl',help='tblout file from hmmsearch') 15 | parser.add_argument('-o','--output',help='output file for normalized results') 16 | parser.add_argument('-tax','--taxonomy',help='taxonomy key containing GTDB accessions and corresponding taxonomy') 17 | 18 | args=parser.parse_args() 19 | cutoff_file=args.csv 20 | hmm_file=args.tbl 21 | out_file=args.output 22 | tax_file=args.taxonomy 23 | 24 | max_score={} 25 | 26 | with open(cutoff_file, 'r') as score: 27 | for line in score: 28 | col=line.strip().split(',') 29 | max_score[col[0]]=[col[1],col[2],col[3]] #adds hmm name as key and list of max score and degradation type as values (Group10_con1_VK_TmoB: [200.7,aerobic,aromatic]) 30 | print(max_score) 31 | 32 | tax_name={} 33 | with open(tax_file, 'r') as tax: 34 | for line in tax: 35 | col=line.strip().split('\t') 36 | tax_name[col[0]]=[col[1]] #adds gtdb accession name as key and list of taxonomy as values (RS_GCF_000980155.1: [d__Archaea;p__Halobacteriota;c__Methanosarcinia;o__Methanosarcinales;f__Methanosarcinaceae;g__Methanosarcina;s__Methanosarcina mazei]) 37 | #print(tax_name) 38 | 39 | 40 | with open (hmm_file, 'r') as hmm, open (out_file, 'a') as out: 41 | for line in hmm: 42 | if not line.startswith('#'): 43 | cols = line.strip().split('\t') #splits on whitespace 44 | if cols[1] in max_score.keys(): 45 | nor_score=float(cols[3])/float(max_score[cols[1]][0]) #normalize the domain score by the max possible domain score for that HMM 46 | metabol=max_score[cols[1]][1] 47 | HC_type=max_score[cols[1]][2] 48 | if cols[0] in tax_name.keys(): 49 | acc_tax=tax_name[cols[0]][0] 50 | out.write(line.strip('\n') + '\t'+ str(round(nor_score,3)) +'\t'+metabol +'\t'+HC_type+'\t'+acc_tax+ '\n') #writes line and normalized score and degradation type at the end 51 | continue 52 | 53 | 54 | -------------------------------------------------------------------------------- /manuscript/.ipynb_checkpoints/Database creation-checkpoint.md: -------------------------------------------------------------------------------- 1 | # **CANT-HYD database commands** 2 | 3 | ## Reference sequence clustering 4 | 5 | 1. Concatenate all reference sequence files 6 | 7 | ```bash 8 | cat *.faa > All_hydrocarbon_reference_sequences.faa 9 | ``` 10 | 11 | 2. Assign reference sequences to clusters of probable functional homology (i.e. homologous groups) 12 | 13 | 1. Create a [BLAST](https://www.ncbi.nlm.nih.gov/books/NBK52640/) database from reference sequence files 14 | 15 | ```bash 16 | makeblastdb -in All_hydrocarbon_reference_sequences.faa -dbtype prot -out Hydrocarbon_reference_sequences.db 17 | ``` 18 | 19 | 2. BLAST reference sequences against the reference sequence BLAST database 20 | 21 | ```bash 22 | blastp -db Hydrocarbon_reference_sequences.db -query All_hydrocarbon_reference_sequences.faa -outfmt 6 -evalue 1e-4 -num_threads 40 -out Self_blast_hydrocarbon_references.txt 23 | ``` 24 | 25 | 3. 26 | 27 | ## Sequence homology search 28 | 29 | 1. Search homologous group sequences against NCBI’s non-redundant protein database in [Diamond](https://github.com/bbuchfink/diamond) format 30 | 31 | ```bash 32 | diamond blastp --db /gpfs/ebg_data/database/nr/nr.dmnd --query All_hydrocarbon_reference_sequences.faa --out diamondout_All_hydrocarbon_reference_sequences.txt --outfmt 6 qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore full_sseq --max-target-seqs 0 --query-cover 70 --evalue 0.0001 --threads 60 33 | ``` 34 | 35 | 2. Add sequences resulting from diamond search to predefined homologous groups 36 | 37 | ```bash 38 | > insert script used to add sequences 39 | ``` 40 | 41 | 3. Remove duplicate sequences using [Usearch](https://www.drive5.com/usearch/) 42 | 43 | ```bash 44 | for file in /gpfs/ebg_work/hackathon/Test/*.faa; do newname=$(basename $file .faa); time usearch -derep_fulllength $file -fastaout $newname.uniques.fasta; done 45 | ``` 46 | 47 | 4. Cluster sequences at 98% similarity using [Usearch](https://www.drive5.com/usearch/) 48 | 49 | ```bash 50 | for file in /gpfs/ebg_work/hackathon/Test/cluster/*.fasta; do newname=$(basename $file .fasta); time usearch -cluster_fast $file -id 0.98 -centroids $newname.98.repseqs.fasta -uc $newname.clusters.uc; done 51 | ``` 52 | 53 | 5. Add reference sequences to the clustered sequence files 54 | 55 | ```bash 56 | grep -A 1 --no-group-separator -w -Ff Test/HomologGroup1.seqID.list Alignment/All_hydrocarbon_reference_sequences_singleline.fasta >> Alignment/Group1.uniques.98.repseqs.fasta 57 | ``` 58 | 59 | ## Phylogenetic tree generation 60 | 61 | 1. Align clustered sequences using [Muscle](https://www.drive5.com/muscle/) 62 | 63 | ```bash 64 | muscle -in Group1.uniques.98.repseqs.fasta -out Group1.uniques.98.repseqs_align.fasta 65 | ``` 66 | 67 | 2. Create phylogentic trees from aligned clustered sequences using [FastTree](http://www.microbesonline.org/fasttree/) 68 | 69 | ```bash 70 | FastTreeMP -pseudo -spr 4 Group1.uniques.98.repseqs_align.fasta > Group1.uniques.98.repseqs_align_tree.tre 71 | ``` 72 | 73 | 3. Visualize trees using [iTOL](https://itol.embl.de/) -------------------------------------------------------------------------------- /manuscript/plotting/allMGs_above_0.8.R: -------------------------------------------------------------------------------- 1 | library(reshape2) 2 | library(dplyr) 3 | library(tidyr) 4 | library(ggplot2) 5 | 6 | setwd("../My Documents/alkanes_hackathon/validation/Metagenomes/normalized_metagenome_hmmsearch_results") 7 | 8 | f <- read.table("./allMG_above_NC_wide.csv", header=TRUE,sep=",") 9 | 10 | f_m <- melt(f,id=c("Metagenome","Environment")) 11 | 12 | write.csv(f_m,"allMG_above_NC_long.csv") 13 | f_m_new <- read.csv("allMG_above_NC_long.csv") 14 | 15 | 16 | #keep order same as original data 17 | f_m_new$variable <- factor(f_m_new$variable,levels = unique(f_m_new$variable)) 18 | 19 | #~~~~~~~~~~~~~~~~~~~~~~~~~~BUBBLE PLOT~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# 20 | 21 | p2 <- ggplot(f_m_new,aes(x=Metagenome,y=variable)) + 22 | geom_point(aes(size = value, colour = class),alpha=0.75)+ 23 | facet_grid(class ~ Environment ,scales = "free",space="free")+ 24 | scale_y_discrete(limits=rev)+ 25 | scale_size_continuous(limits=c(0.000011,0.03),range = c(1.5,12),breaks=c(0.00001,0.0001,0.001,0.01,0.1))+ 26 | labs(size="# of Hits",colour="HMM Metabolism Classification") + 27 | theme(axis.text.y=element_text(colour="#31393C",size=12), 28 | axis.ticks.y=element_blank(), 29 | axis.title=element_blank(), 30 | axis.text.x=element_text(angle=90,hjust=1,vjust=0.3, colour="#31393C",size=12), 31 | legend.title = element_text(size = 12), panel.background = element_blank(), 32 | legend.text = element_text(size=12,color = "#31393C"), 33 | panel.border = element_rect(colour = "#e6e6e6ff", fill = NA, size = 1.2), 34 | legend.position = "right", 35 | legend.background = element_blank(), 36 | panel.grid.major.y = element_line(colour = "#fafafaff"), 37 | panel.grid.major.x = element_line(colour="#fafafaff"), 38 | strip.text.y = element_text(colour="black",size=12,angle=0), 39 | strip.background = element_rect(fill = "#f2f2f2ff",color = "#fafafaff"))+ 40 | scale_color_manual(values = c("#3381FF","#ADDAFF","#EC8609","#FED872"), guide = guide_legend(override.aes = list(size=5))) 41 | 42 | p2 43 | 44 | #~~~~~~~~~~~~~~~~~~~~~~~~~~HEATMAP PLOT~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# 45 | 46 | library(ggdendro) 47 | library(grid) 48 | library(dendextend) 49 | 50 | rownames(f) <- f$Metagenome 51 | 52 | d <- dist(f,method="euclidean") 53 | h <- as.dendrogram(hclust(d,method = "average")) 54 | 55 | mg_dendro <- ggdendrogram(data=h,rotate=TRUE)+ 56 | theme(axis.text.y=element_text(size=10,colour = "#31393C")) 57 | 58 | mg_dendro 59 | 60 | dend_1 <- f %>% dist %>% hclust %>% as.dendrogram %>% set("labels_cex",0) %>% set("branches_lwd",0.5) %>% set("hang_leaves") 61 | 62 | mg_dendro <- ggdendrogram(data=dend_1,rotate=TRUE)+ 63 | theme(axis.text.y=element_text(size=10,colour = "#31393C")) 64 | 65 | plot(mg_dendro) 66 | 67 | f_m_new$Metagenome <- factor(f_m_new$Metagenome,levels=labels(dend_1),ordered = TRUE) 68 | 69 | 70 | 71 | p1 <- ggplot(f_m_new,aes(x=variable,y=Metagenome), fill=value)+ 72 | geom_tile(aes(fill=value))+ 73 | theme(axis.title=element_blank(), 74 | axis.text.x = element_text(angle=90, size=10,colour="#31393C",hjust=1,vjust=0.3), 75 | #axis.text.y=element_blank(), 76 | axis.text.y = element_text(size=8,colour="#31393C"), 77 | legend.position = "none", 78 | legend.text=element_text(size=8,colour="#31393C"))+ 79 | scale_fill_gradient(high = "#EC8609",low = "#FFFFFF",na.value = "#FFFFFF", trans="log10") 80 | 81 | 82 | #scale_fill_gradient(colours=my_palette,breaks=my_breaks)+ 83 | #coord_flip()#+ 84 | #labs(title = "Mixed Metagenomes, norcutoff >=0.8",value="Counts of gene expression") 85 | 86 | p1 87 | 88 | #putting plots together 89 | grid.newpage() 90 | print(p1,vp=viewport(x = 0.3, y = 0.5, width = 0.6, height = 1.0)) 91 | print(mg_dendro, vp = viewport(x = 0.8, y = 0.69, width = 0.4, height = 0.63)) 92 | -------------------------------------------------------------------------------- /manuscript/Database creation.md: -------------------------------------------------------------------------------- 1 | # **CANT-HYD database commands** 2 | 3 | ## Reference sequence clustering 4 | 5 | 1. Concatenate all reference sequence files 6 | 7 | ```bash 8 | cat *.faa > All_hydrocarbon_reference_sequences.faa 9 | ``` 10 | 11 | 2. Assign reference sequences to clusters of probable functional homology (i.e. homologous groups) 12 | 13 | 1. Create a [BLAST](https://www.ncbi.nlm.nih.gov/books/NBK52640/) database from reference sequence files 14 | 15 | ```bash 16 | makeblastdb -in All_hydrocarbon_reference_sequences.faa -dbtype prot -out Hydrocarbon_reference_sequences.db 17 | ``` 18 | 19 | 2. BLAST reference sequences against the reference sequence BLAST database 20 | 21 | ```bash 22 | blastp -db Hydrocarbon_reference_sequences.db -query All_hydrocarbon_reference_sequences.faa -outfmt 6 -evalue 1e-4 -num_threads 40 -out Self_blast_hydrocarbon_references.txt 23 | ``` 24 | 25 | 3. Cluster at 20% sequence identity 26 | 27 |
28 | Show code 29 |

30 | 31 | ```bash 32 | #!/usr/bin/perl 33 | 34 | use strict; 35 | 36 | my(@homolog,%homo,%homoCheck,@done,%seqID, %seqNO, %hasHomolog) = (); 37 | open(IN,$ARGV[0]) or die "Can't open input file\n"; 38 | open(IN2,$ARGV[1]) or die "Can't open acc file\n"; 39 | my $count = 0; 40 | while(my $line = ){ 41 | chomp($line); 42 | $seqID{$line} = $count; 43 | $seqNO{$count} = $line; 44 | $count++; 45 | } 46 | 47 | while(my $line = ){ 48 | chomp($line); 49 | my @junk = split("\t",$line); 50 | if($junk[0] ne $junk[1]){ 51 | if($junk[2] >= 25 && $junk[10] <= 0.0001){ 52 | $homolog[$seqID{$junk[0]}][$seqID{$junk[1]}] = 1; 53 | } 54 | } 55 | } 56 | for(my $i=0; $i < $count; $i++){ 57 | my $seq1 = $seqNO{$i}; 58 | for(my $j=0; $j < $count; $j++){ 59 | my $seq2 = $seqNO{$j}; 60 | if($seq1 ne $seq2){ 61 | if($homolog[$i][$j]){ #If homolog exists between seq1 and seq2 62 | if($homoCheck{$seq1}){ #if the seq1 already has a homolog 63 | if($homoCheck{$seq2}){ #does seq2 also, the do nothing 64 | if($homoCheck{$seq1} ne $homoCheck{$seq2}){ #Check if they are not part of same cluster 65 | $homo{$homoCheck{$seq1}} = $homo{$homoCheck{$seq1}}."XXYYZZ".$homo{$homoCheck{$seq2}}; 66 | delete($homo{$homoCheck{$seq2}}); 67 | foreach my $key (keys %homoCheck){ 68 | if($homoCheck{$key} eq $homoCheck{$seq2}){ 69 | $homoCheck{$key} = $homoCheck{$seq1}; 70 | } 71 | } 72 | #print "OOOOOOO:$homoCheck{$seq1} $homoCheck{$seq2}\n"; 73 | } 74 | } 75 | else{ #If seq2 doesn't 76 | my $h = $homoCheck{$seq1}; #find which sequence is seq1 homolog of 77 | $homo{$h} = $homo{$h}."XXYYZZ".$seq2; #and append seq2 to the list of homologs that seq1 belongs to 78 | $homoCheck{$seq2} = $h; #and add seq2 to homolog check 79 | } 80 | } 81 | else{ #if seq1 has not been detected as homolog os anything 82 | if($homoCheck{$seq2}){ # But seq2 has 83 | my $h = $homoCheck{$seq2}; #find which sequence is seq2 homolog of 84 | $homo{$h} = $homo{$h}."XXYYZZ".$seq1; #append seq1 to the list os homologs that seq2 belongs to 85 | $homoCheck{$seq1} = $h; #and add seq1 to the homolog check 86 | } 87 | else{ #if seq2 also doens't belong to any other homologs as well 88 | if($homo{$seq1}){ 89 | $homo{$seq1} = $homo{$seq1}."XXYYZZ".$seq2; 90 | } 91 | else{ 92 | $homo{$seq1} = $seq2; 93 | } 94 | $homoCheck{$seq2} = $seq1; #add seqs2 homolog check 95 | } 96 | } 97 | } 98 | } 99 | } 100 | } 101 | my $filenum=1; 102 | my $selfCheck; 103 | foreach my $key (keys %homo){ 104 | my $outfilename = "HomologGroup".$filenum.".seqID.list"; 105 | open(OUT,">$outfilename") or die "Can't create $outfilename\n"; 106 | my $list = $homo{$key}; 107 | my @outList = split(/XXYYZZ/,$list); 108 | foreach my $outID (@outList){ 109 | if($outID){ 110 | print OUT "$outID\n"; 111 | $hasHomolog{$outID}++; 112 | if($outID eq $key){ $selfCheck = 1; } 113 | } 114 | } 115 | if($selfCheck){} 116 | else{ print OUT "$key\n"; } 117 | $selfCheck = 0; 118 | $filenum++; 119 | } 120 | open(SIG,">SingletonHomolog.list"); 121 | for(my $i=0; $i < $count; $i++){ 122 | if(!($hasHomolog{$seqNO{$i}})){ 123 | my $outfilename = "HomologGroup".$filenum.".seqID.list"; 124 | open(OUT,">$outfilename") or die "Can't create $outfilename\n"; 125 | print OUT "$seqNO{$i}\n"; 126 | print SIG "$seqNO{$i}\n"; 127 | $filenum++; 128 | } 129 | } 130 | ``` 131 | 132 |

133 | 134 | ## Sequence homology search 135 | 136 | 1. Search homologous group sequences against NCBI’s non-redundant protein database in [Diamond](https://github.com/bbuchfink/diamond) format 137 | 138 | ```bash 139 | diamond blastp --db /gpfs/ebg_data/database/nr/nr.dmnd --query All_hydrocarbon_reference_sequences.faa --out diamondout_All_hydrocarbon_reference_sequences.txt --outfmt 6 qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore full_sseq --max-target-seqs 0 --query-cover 70 --evalue 0.0001 --threads 60 140 | ``` 141 | 142 | 2. Add sequences resulting from diamond search to predefined homologous groups 143 | 144 |
145 | Show code 146 |

147 | 148 | ```bash 149 | #! usr/pyenv/python3 150 | 151 | import glob,re,os,sys 152 | from pathlib import Path 153 | 154 | blast_file="/gpfs/ebg_work/hackathon/diamond/diamondout_All_hydrocarbon_reference_sequences.txt" 155 | 156 | def make_fasta(f_path,out): 157 | with open(f_path,'r') as group,open(blast_file,'r') as blast, open(out, 'a') as fasta: 158 | seqid=[] 159 | 160 | for line in group: 161 | line=line.strip('\n') 162 | seqid.append(line) 163 | print(seqid) 164 | 165 | for line in blast: 166 | cols=line.split('\t') 167 | #print(cols) 168 | if cols[0] in seqid: 169 | print(cols[0]) 170 | fasta.write('>' + cols[1] + '\n' + cols[12] + '\n') 171 | return; 172 | 173 | def main(): 174 | import re 175 | directory=sys.argv[1] 176 | groups=[] 177 | for file in os.listdir(directory): 178 | if file.startswith("Homolog"): 179 | groups.append(file) 180 | print(groups) 181 | 182 | for f in groups: 183 | print(f) 184 | g_num=int(''.join(filter(str.isdigit,f))) 185 | fpath=f"{directory}/{f}" 186 | out=f"{directory}/Group{g_num}.faa" 187 | make_fasta(fpath,out) 188 | main() 189 | ``` 190 | 191 |

192 | 193 | 3. Remove duplicate sequences using [Usearch](https://www.drive5.com/usearch/) 194 | 195 | ```bash 196 | for file in /gpfs/ebg_work/hackathon/Test/*.faa; do newname=$(basename $file .faa); time usearch -derep_fulllength $file -fastaout $newname.uniques.fasta; done 197 | ``` 198 | 199 | 4. Cluster sequences at 98% similarity using [Usearch](https://www.drive5.com/usearch/) 200 | 201 | ```bash 202 | for file in /gpfs/ebg_work/hackathon/Test/cluster/*.fasta; do newname=$(basename $file .fasta); time usearch -cluster_fast $file -id 0.98 -centroids $newname.98.repseqs.fasta -uc $newname.clusters.uc; done 203 | ``` 204 | 205 | 5. Add reference sequences to the clustered sequence files 206 | 207 | ```bash 208 | grep -A 1 --no-group-separator -w -Ff Test/HomologGroup1.seqID.list Alignment/All_hydrocarbon_reference_sequences_singleline.fasta >> Alignment/Group1.uniques.98.repseqs.fasta 209 | ``` 210 | 211 | ## Phylogenetic tree generation 212 | 213 | 1. Align clustered sequences using [Muscle](https://www.drive5.com/muscle/) 214 | 215 | ```bash 216 | muscle -in Group1.uniques.98.repseqs.fasta -out Group1.uniques.98.repseqs_align.fasta 217 | ``` 218 | 219 | 2. Create phylogentic trees from aligned clustered sequences using [FastTree](http://www.microbesonline.org/fasttree/) 220 | 221 | ```bash 222 | FastTreeMP -pseudo -spr 4 Group1.uniques.98.repseqs_align.fasta > Group1.uniques.98.repseqs_align_tree.tre 223 | ``` 224 | 225 | 3. Visualize trees using [iTOL](https://itol.embl.de/) -------------------------------------------------------------------------------- /manuscript/plotting/GTDB_summary_table_data_manipulation.r: -------------------------------------------------------------------------------- 1 | #set working directory and load tidyverse package 2 | setwd("~/University of Calgary/PhD/hackathon/HMM_testing/GTDB_Final_HMMs") 3 | library(tidyverse) 4 | 5 | #read in table from normalize_hmm_scores_taxonomy_and_metadata.py script 6 | jz = read.table("GTDB_domain_scores_metadata.txt", header = FALSE) 7 | 8 | #read in cutoff scores 9 | cut = read.csv("cutoff_score.csv", header = TRUE) 10 | 11 | 12 | #add column names 13 | colnames(jz) = c("Genome", "HMM", "evalue", "score", "accession", "norm_score", "oxygen", "HC", "taxonomy", "species") 14 | 15 | 16 | #join cutoff scores with GTDB results using HMM name 17 | jz_cut = left_join(jz, cut, by = "HMM") 18 | 19 | #delete rows with a score less than the noise score 20 | jz_cut2 = jz_cut %>% filter(score > Noise) 21 | 22 | #delete rows with a score less than the threshold 23 | #jz_cut2 = jz_cut %>% filter(score > Threshold) 24 | 25 | #get rid of weird species column 26 | jz3 = jz_cut2 %>% select(-species) 27 | 28 | #split taxonomy into separate columns 29 | jz4 = jz3 %>% separate(taxonomy, c("Domain", "Phylum", "Class", "Order", "Family", "Genus", "Species"), sep = ";") 30 | 31 | #get rid of underscores in phylum names 32 | jz4$Phylum <- gsub('p__', '', jz4$Phylum) 33 | 34 | #get rid of long HMM name 35 | jz4$HMM <- gsub('Group[0-9][0-9]_con[0-9]_[A-Z][A-Z]_', '', jz4$HMM) 36 | jz4$HMM <- gsub('Group[0-9][0-9]_con[0-9]_', '', jz4$HMM) 37 | jz4$HMM <- gsub('Group[0-9]_con[0-9]_[A-Z][A-Z]_', '', jz4$HMM) 38 | jz4$HMM <- gsub('non_NdoB_type_Naphthalene_Dioxygenase_Alpha', 'non_NdoB_type', jz4$HMM) 39 | jz4$HMM <- gsub('RingHydroxylatingDioxygenase_Alpha', 'RingDioxygenase_alpha', jz4$HMM) 40 | jz4$HMM <- gsub('RingHydroxylating_dioxygenases_beta', 'RingDioxygenase_beta', jz4$HMM) 41 | jz4$HMM <- gsub('MonoAromatic_bphA_tcbA_ipbA_bnzA', 'Monoaromatics_Alpha', jz4$HMM) 42 | jz4$HMM <- gsub('MAH_tcbAb_todC2_bphAb', 'Monoaromatics_Beta', jz4$HMM) 43 | 44 | 45 | #select or exclude specific phylum 46 | jz5 = jz4 %>% filter(Phylum != "Proteobacteria" & Phylum != "Actinobacteriota") 47 | jz5 = jz4 %>% filter(Phylum != "Proteobacteria" & Phylum != "Actinobacteriota" & Phylum != "Firmicutes" & Phylum != "Bacteroidota") 48 | jz5 = jz4 %>% filter(Phylum == "Asgardarchaeota") 49 | 50 | 51 | 52 | ############HMM Frequency count plot 53 | hmm_freq = as.data.frame(summary(as.factor(jz4$HMM))) 54 | colnames(hmm_freq) = c("count_noise") 55 | hmm_freq$HMM = rownames(hmm_freq) 56 | 57 | xx = ggplot(hmm_freq, aes(x = HMM, y = log10(count_noise), fill = count_noise < 10)) + geom_bar(stat = "identity", colour = "black") + labs(x = "", y = "Number of GTDB hits > NC", fill = "") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1, size = 7), axis.title.x = element_blank(), legend.position = "top", legend.text = element_text(size = 10), panel.background = element_blank(), panel.border = element_rect(fill = NA, colour = "grey30")) + scale_y_continuous(expand = c(0,0), limits = c(0,4.4)) + scale_fill_manual(values = c('grey', 'red'), labels = c("> 10 hits", "< 10 hits")) 58 | 59 | 60 | 61 | ##################Phyla frequency plots 62 | ###normalize phylum hits to number of phyla reps in GTDB database 63 | bac = read.table("bac120_taxonomy.tsv") 64 | 65 | bac2 = bac[,1: ncol(bac)-1] 66 | 67 | #split taxonomy into separate columns 68 | bac3 = bac2 %>% separate(V2, c("Domain", "Phylum", "Class", "Order", "Family", "Genus", "Species"), sep = ";") 69 | 70 | #get rid of underscores in phylum names 71 | bac3$Phylum <- gsub('p__', '', bac3$Phylum) 72 | 73 | 74 | #create summary database 75 | phyla_freq = as.data.frame(summary(as.factor(bac3$Phylum), maxsum = 150)) 76 | colnames(phyla_freq) = c("count") 77 | phyla_freq$Phylum = rownames(phyla_freq) 78 | 79 | 80 | #optional: archaea phyla frequency plot 81 | arc = read.table("ar122_taxonomy.tsv") 82 | arc2 = arc[,1: ncol(arc)-1] 83 | arc3 = arc2 %>% separate(V2, c("Domain", "Phylum", "Class", "Order", "Family", "Genus", "Species"), sep = ";") 84 | arc3$Phylum <- gsub('p__', '', arc3$Phylum) 85 | #create summary database 86 | phyla_freq = as.data.frame(summary(as.factor(arc3$Phylum), maxsum = 150)) 87 | colnames(phyla_freq) = c("count") 88 | phyla_freq$Phylum = rownames(phyla_freq) 89 | 90 | 91 | #reduce df to only unique accessions - acc_score_count contains number of hits above noise for each accession 92 | jz_single = jz4 %>% group_by(Genome, Phylum) %>% summarize(acc_score_count = n()) 93 | 94 | #reduce df to only unique phyla - phylum_score_count contains number of hits above noise for each phylum (only one per species allowed) 95 | jz_single2 = jz_single %>% group_by(Phylum) %>% summarize(phylum_score_count = n()) 96 | 97 | #join phyla summary database with norm. score domain by phylum summary table 98 | new_phyla = left_join(phyla_freq, jz_single2, by = "Phylum") 99 | 100 | 101 | #create column with percent of gtdb reps from phyla with hits above noise -- doesn't take into account that there might be multiple hits in the same species 102 | new_phyla$percent_gtdb = (new_phyla$phylum_score_count/new_phyla$count)*100 103 | 104 | 105 | #get rid of NAs 106 | new_phyla2 = new_phyla %>% filter(phylum_score_count != "NA") 107 | 108 | 109 | #plot 110 | gg = ggplot(new_phyla2, aes(y = Phylum, x = (percent_gtdb), colour = percent_gtdb > 20)) + geom_point(aes(size = (count)), alpha = 0.3) + theme(axis.text.y = element_text(size = 10), panel.background = element_blank(), panel.border = element_rect(fill = NA, colour = "grey60"), panel.grid.major = element_line(colour = "grey99"), legend.box = "vertical", legend.position = "top", legend.spacing.y = unit(0.1, "cm"), legend.key = element_blank()) + labs(x = "HMM hits above NC per phylum as ratio of phyla reps in GTDB", y = "", colour = "% of reps in Phyla with HMM hit", size = "Number of reps in GTDB") + scale_colour_manual(values = c("black", "red"), labels = c("< 20%", "> 20%")) + scale_radius(range = c(1,7), trans = 'log10') + geom_text(aes(label = round(percent_gtdb,2))) 111 | 112 | #add colours to axis text 113 | new_phyla2$Phylum <- factor(new_phyla2$Phylum,levels=unique(new_phyla2$Phylum)) 114 | con <- ifelse(new_phyla2$percent_gtdb >= 15, 'red', 'black') 115 | con2 = rev(con) 116 | 117 | 118 | gg = ggplot(new_phyla2, aes(y = Phylum, x = (percent_gtdb), colour = percent_gtdb > 20)) + geom_point(aes(size = (count)), alpha = 0.7) + theme(axis.text.y = element_text(size = 9.5, colour = rev(con)), panel.background = element_blank(), panel.border = element_rect(fill = NA, colour = "grey60"), panel.grid.major = element_line(colour = "grey99"), legend.box = "vertical", legend.position = "top", legend.spacing.y = unit(0.1, "cm"), legend.key = element_blank()) + labs(x = "HMM hits (>0.8) per phylum normalized to phyla reps in GTDB", y = "", colour = "% of reps in GTDB with HMM hit", size = "Number of reps in GTDB") + scale_colour_manual(values = c("black", "red"), labels = c("< 20%", "> 20%")) + scale_radius(range = c(1,7), trans = 'log10') + scale_y_discrete(limits = rev(levels(new_phyla2$Phylum))) 119 | 120 | 121 | #####HMM distribution in phyla 122 | #order the dataframe based on accession and highest normalized score to noise 123 | aa <- jz4[order( jz4$score/jz4$Noise, jz4$accession, decreasing = TRUE), ] 124 | #select only unique accessions (first in list which should have the highest normalized score) 125 | bb = aa[ !duplicated(aa$accession), ] 126 | 127 | #reduce df to only unique accessions - acc_score_count contains number of hits > Noise for each accession 128 | jz_single = bb %>% select(Phylum, HMM, score, oxygen, HC, Threshold, Noise) %>% group_by(Phylum, HMM, oxygen, HC, Threshold, Noise) %>% summarize(hmm_score_count = n(), mean_score = mean(score) ) 129 | 130 | 131 | #join phyla summary database with norm. score domain by phylum summary table 132 | new_phyla = left_join(phyla_freq, jz_single, by = "Phylum") 133 | #get rid of NAs 134 | new_phyla2 = new_phyla %>% filter(hmm_score_count != "NA") 135 | 136 | new_phyla2$oxygen_HC = paste(new_phyla2$oxygen,new_phyla2$HC,sep=" ") 137 | 138 | #cluster phyla based on HMM hits 139 | library(vegan) 140 | clust_phyla = data.frame(Phylum = new_phyla2$Phylum, HMM = new_phyla2$HMM, hmm_score_count = as.numeric(new_phyla2$hmm_score_count)) 141 | #make data frame wide 142 | clust_phyla_wide = pivot_wider(clust_phyla, names_from = HMM, values_from = hmm_score_count) 143 | #turn NA into zeroes 144 | clust_phyla_wide[is.na(clust_phyla_wide)] = 0 145 | 146 | #create matrix for distance clustering 147 | clustm = as.matrix(clust_phyla_wide[,2:ncol(clust_phyla_wide)]) 148 | row.names(clustm) = clust_phyla_wide$Phylum 149 | phyl_dist = vegdist(clustm, method= "jaccard") 150 | phyl_clust = as.dendrogram(hclust(phyl_dist, method = "average")) 151 | plot(phyl_clust) 152 | 153 | 154 | new_phyla3 = new_phyla2 155 | 156 | new_phyla3$Phylum = factor(new_phyla3$Phylum, levels = labels(phyl_clust), ordered = TRUE) 157 | 158 | 159 | xx = ggplot(new_phyla3,aes(x = Phylum, y = reorder(HMM, desc(HMM)))) + geom_point(aes(size = hmm_score_count, colour = oxygen_HC), alpha = 0.9) + facet_grid(oxygen_HC~., space = "free", scales = "free_y") + theme(axis.text.x = element_text(size = 10, angle = 90, vjust = 0.3, hjust = 1, colour = "grey30"), axis.text.y = element_text(size = 9, colour= "grey30"), axis.ticks = element_line(colour = "grey30"), strip.text.y = element_text(angle = 0), strip.background = element_rect(fill = "grey95", colour = "grey90"), legend.background = element_blank(), panel.grid.major = element_line(colour = "grey98"), legend.key = element_blank(), panel.background = element_blank(), panel.border = element_rect(fill = NA, colour ="grey90"), legend.position = "top") + labs(x = "", y = "", size = "Number of HMM hits") + scale_colour_manual(guide = "none", values = c("#3381ff", "#addaff", "#ec8609", "#fed872")) + scale_size_continuous(breaks = c(1, 10, 100, 1000), trans = "log10", range = c(1,4)) 160 | 161 | ###GTDB reps vs hits relationship 162 | 163 | p = ggplot(new_phyla2, aes(x = count, y = phylum_score_count)) + geom_smooth(method = "lm", colour = "black", alpha = 0.15)+ geom_point(size = 4, alpha =0.6) + scale_x_continuous(trans = "log",breaks = c(1,10,100,1000,10000,100000)) + scale_y_continuous(trans = "log", breaks = c(1,10,100,1000,10000)) + labs(x = "GTDB reps", y = "HMM hits") + scale_colour_manual(values = colours) + theme(axis.text.y = element_text(size = 10), panel.background = element_blank(), panel.border = element_rect(fill = NA, colour = "grey60"), panel.grid.major = element_line(colour = "grey99"), legend.box = "vertical", legend.position = "none", legend.spacing.y = unit(0.1, "cm"), legend.key = element_blank()) + geom_text(aes(label = Phylum), alpha = 0.5, size =2.5, colour = "grey40") 164 | 165 | #GTDB reps vs hits relationship - black 166 | p = ggplot(new_phyla2, aes(x = count, y = phylum_score_count)) + geom_smooth(method = "lm", colour = "grey80", alpha = 0.05)+ geom_point(size = 4, alpha =0.6) + scale_x_continuous(trans = "log",breaks = c(1,10,100,1000,10000,100000)) + scale_y_continuous(trans = "log", breaks = c(1,10,100,1000,10000, 100000)) + labs(x = "GTDB reps", y = "HMM hits") + theme(axis.text.y = element_text(size = 10), panel.background = element_blank(), panel.border = element_rect(fill = NA, colour = "grey60"), panel.grid.major = element_line(colour = "grey99"), legend.box = "vertical", legend.position = "none", legend.spacing.y = unit(0.1, "cm"), legend.key = element_blank()) + geom_text(aes(label = Phylum, y = phylum_score_count+(phylum_score_count/5)), alpha = 0.65, size =2.5, colour = "grey20") + coord_equal() 167 | 168 | 169 | ###########Cyanobacteria LadA 170 | 171 | jz5 = jz4 %>% filter(Phylum == "Cyanobacteria") 172 | jz6 = jz5 %>% filter(HMM == "LadA_beta") 173 | jz6$Genus <- gsub('g__', '', jz6$Genus) 174 | jz6$Family <- gsub('f__', '', jz6$Family) 175 | jz6$Genus <- gsub('_.', '', jz6$Genus) 176 | 177 | #make Cyanobacteria genus figure 178 | 179 | xx = ggplot(jz6, aes(x = score, y = reorder(Genus, desc(Genus)))) + geom_point(size = 3, alpha = 0.5) + theme(axis.text.x = element_text(size = 10, colour = "grey30"), axis.text.y = element_text(size = 9, colour= "grey30"), axis.ticks = element_line(colour = "grey30"), panel.grid.major = element_line(colour = "grey98"), panel.background = element_blank(), panel.border = element_rect(fill = NA, colour ="grey90"), axis.title.x = element_text(colour = "grey30", face = "bold")) + labs(x = "LadA beta HMM score", y = "") 180 | 181 | #horizontal 182 | xx = ggplot(jz6, aes(y = score, x= Genus)) + geom_point(size = 3, alpha = 0.55) + theme(axis.text.x = element_text(angle = 90, vjust = 0.3, hjust = 1, size = 10, colour = "grey30"), axis.text.y = element_text(size = 9, colour= "grey30"), axis.ticks = element_line(colour = "grey30"), panel.grid.major = element_line(colour = "grey98"), panel.background = element_blank(), panel.border = element_rect(fill = NA, colour ="grey90"), axis.title.y = element_text(colour = "grey30", face = "bold"), legend.text = element_text(size = 9, colour = "grey30"), legend.position = "top", legend.key = element_blank()) + labs(y = "LadA beta HMM score", x = "", colour = "") 183 | 184 | #add colours for family 185 | xx = ggplot(jz6, aes(x = score, y = reorder(Genus, desc(Genus)))) + geom_point(size = 3, alpha = 0.85, aes(colour = Family)) + theme(axis.text.x = element_text(size = 10, colour = "grey30"), axis.text.y = element_text(size = 9, colour= "grey30"), axis.ticks = element_line(colour = "grey30"), panel.grid.major = element_line(colour = "grey98"), panel.background = element_blank(), panel.border = element_rect(fill = NA, colour ="grey90"), axis.title.x = element_text(colour = "grey30", face = "bold"), legend.text = element_text(size = 9, colour = "grey30"), legend.title = element_text(colour = "grey30"), legend.position = "right", legend.key = element_blank()) + labs(x = "LadA beta HMM score", y = "") + scale_colour_manual(values = c("#173A17", "#3A7132", "#84C072", "#C6E7C6")) 186 | 187 | #horizontal 188 | xx = ggplot(jz6, aes(y = score, x= Genus)) + geom_point(size = 3, alpha = 0.85, aes(colour = Family)) + theme(axis.text.x = element_text(angle = 90, vjust = 0.3, hjust = 1, size = 10, colour = "grey30"), axis.text.y = element_text(size = 9, colour= "grey30"), axis.ticks = element_line(colour = "grey30"), panel.grid.major = element_line(colour = "grey98"), panel.background = element_blank(), panel.border = element_rect(fill = NA, colour ="grey90"), axis.title.y = element_text(colour = "grey30", face = "bold"), legend.text = element_text(size = 9, colour = "grey30"), legend.position = "top", legend.key = element_blank()) + labs(y = "LadA beta HMM score", x = "", colour = "") + scale_colour_manual(values = c("#173A17", "#3A7132", "#84C072", "#C6E7C6")) 189 | 190 | #concatenate cyanobacteria genome list 191 | new = as.data.frame(summary(as.factor(jz7$Genome))) 192 | write.csv(new, "Cyano_ladA-beta_genome.csv") 193 | sed 's/\r$//' cyano_genome_ladA_list.txt > cyano_genome_ladA_list.UNIX.list  194 | #in bash 195 | for file in $(<../../cyano_genomes/cyano_genome_ladA_list.UNIX.list ); do cp "$file" ../../cyano_genomes/; done 196 | #### fix gene headers so that they contain organsim accession ### 197 | 198 | for var in *.faa; do sed 's/>/>'$var'_/g' $var > 'Header_'$var;done 199 | 200 | cat Header* > cyano_ladA_cat_genomes.fasta 201 | 202 | #convert to single line fasta file 203 | awk '{if(NR==1) {print $0} else {if($0 ~ /^>/) {print "\n"$0} else {printf $0}}}' cyano_ladA_cat_genomes.fasta > cyano_ladA_genomes_singleline.fasta 204 | 205 | 206 | #collect ladA sequences - need to add extra spaces for grep command 207 | new2 = as.data.frame(summary(as.factor(jz6$accession),maxsum = 160)) 208 | write.csv(new2, "Cyano_ladA-beta_accession.csv") 209 | sed 's/\r$//' cyano_accession_ladA_list.txt > cyano_accession_ladA_list.UNIX.txt 210 | grep -A1 -f cyano_accession_ladA_list.UNIX.txt cyano_ladA_genomes_singleline.fasta --no-group-separator > cyano_ladA_accessions_seqs.fasta 211 | 212 | #add lad ref seqs back in - need to add new lines between fasta files 213 | #98% clusters 214 | cat cyano_ladA_accessions_seqs.fasta ../../../JZ/LadA_redo/Group8.ladA_beta.98.repseqs.fasta ../../../JZ/LadA_redo/Group8.ladA_alpha.98.repseqs.fasta ../../../JZ/LadA_redo/Group8.ladB.98.repseqs.fasta > lad_cyano_seqs_98.fasta 215 | 216 | 217 | #only seqs used for HMM 218 | cat cyano_ladA_accessions_seqs.fasta ../../../HMM/for_HMM_alignment/Supplementary_Data_HMM_Fastas/Group8_con1_JZ_LadA_alpha.fasta ../../../HMM/for_HMM_alignment/Supplementary_Data_HMM_Fastas/Group8_con1_JZ_LadA_beta.fasta ../../../HMM/for_HMM_alignment/Supplementary_Data_HMM_Fastas/Group8_con1_JZ_LadB.fasta > cyano_ladA_plus_lad_HMM_seqs.fasta 219 | 220 | #shorten long gene names 221 | sed 's/\#.*//g' cyano_ladA_plus_lad_HMM_seqs.fasta > test_cyano_ladA_plus_lad_HMM_seqs.fasta 222 | 223 | #cluster at 70% ID 224 | usearch -cluster_fast test_lad_cyano_seqs_98.fasta -id 0.70 -centroids test_lad_cyano_seqs_70.fasta -uc test_lad_cyano_seqs_70.clusters.uc 225 | 226 | #add EXP sequences back in 227 | 228 | #muscle alignment 229 | muscle -in test_cyano_ladA_plus_lad_HMM_seqs.fasta -out test_cyano_ladA_plus_lad_HMM_seqs_align.fasta 230 | 231 | -------------------------------------------------------------------------------- /License: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . -------------------------------------------------------------------------------- /.ipynb_checkpoints/License-checkpoint: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. By contrast, 15 | the GNU General Public License is intended to guarantee your freedom to 16 | share and change all versions of a program--to make sure it remains free 17 | software for all its users. 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No Surrender of Others' Freedom. 541 | 542 | If conditions are imposed on you (whether by court order, agreement or 543 | otherwise) that contradict the conditions of this License, they do not 544 | excuse you from the conditions of this License. If you cannot convey a 545 | covered work so as to satisfy simultaneously your obligations under this 546 | License and any other pertinent obligations, then as a consequence you may 547 | not convey it at all. For example, if you agree to terms that obligate you 548 | to collect a royalty for further conveying from those to whom you convey 549 | the Program, the only way you could satisfy both those terms and this 550 | License would be to refrain entirely from conveying the Program. 551 | 552 | 13. Use with the GNU Affero General Public License. 553 | 554 | Notwithstanding any other provision of this License, you have 555 | permission to link or combine any covered work with a work licensed 556 | under version 3 of the GNU Affero General Public License into a single 557 | combined work, and to convey the resulting work. The terms of this 558 | License will continue to apply to the part which is the covered work, 559 | but the special requirements of the GNU Affero General Public License, 560 | section 13, concerning interaction through a network will apply to the 561 | combination as such. 562 | 563 | 14. Revised Versions of this License. 564 | 565 | The Free Software Foundation may publish revised and/or new versions of 566 | the GNU General Public License from time to time. Such new versions will 567 | be similar in spirit to the present version, but may differ in detail to 568 | address new problems or concerns. 569 | 570 | Each version is given a distinguishing version number. If the 571 | Program specifies that a certain numbered version of the GNU General 572 | Public License "or any later version" applies to it, you have the 573 | option of following the terms and conditions either of that numbered 574 | version or of any later version published by the Free Software 575 | Foundation. If the Program does not specify a version number of the 576 | GNU General Public License, you may choose any version ever published 577 | by the Free Software Foundation. 578 | 579 | If the Program specifies that a proxy can decide which future 580 | versions of the GNU General Public License can be used, that proxy's 581 | public statement of acceptance of a version permanently authorizes you 582 | to choose that version for the Program. 583 | 584 | Later license versions may give you additional or different 585 | permissions. However, no additional obligations are imposed on any 586 | author or copyright holder as a result of your choosing to follow a 587 | later version. 588 | 589 | 15. Disclaimer of Warranty. 590 | 591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT 593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY 594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, 595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 596 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM 597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF 598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION. 599 | 600 | 16. Limitation of Liability. 601 | 602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS 604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY 605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE 606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF 607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD 608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), 609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF 610 | SUCH DAMAGES. 611 | 612 | 17. Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . -------------------------------------------------------------------------------- /HMMs/individual HMMs/TmoB_BmoB.hmm: -------------------------------------------------------------------------------- 1 | HMMER3/f [3.2.1 | June 2018] 2 | NAME TmoB_BmoB 3 | DESC toluene monooxygenase subunit B 4 | LENG 88 5 | ALPH amino 6 | RF no 7 | MM no 8 | CONS yes 9 | CS no 10 | MAP yes 11 | DATE Tue Nov 24 14:20:23 2020 12 | NSEQ 207 13 | EFFN 2.068863 14 | CKSUM 3236614396 15 | TC 180 180; 16 | NC 140 140; 17 | STATS LOCAL MSV -9.1206 0.71844 18 | STATS LOCAL VITERBI -9.8562 0.71844 19 | STATS LOCAL FORWARD -3.9935 0.71844 20 | HMM A C D E F G H I K L M N P Q R S T V W Y 21 | m->m m->i m->d i->m i->i d->m d->d 22 | COMPO 2.43221 4.59229 2.76989 2.66357 3.19406 2.99492 3.58863 2.92542 2.79306 2.56204 3.57155 3.18018 3.15409 3.08687 2.94661 2.76188 2.88488 2.33607 4.91979 3.67362 23 | 2.68453 4.42365 2.77523 2.73118 3.46494 2.40604 3.72297 3.29473 2.67838 2.69395 4.24385 2.90373 2.73691 3.18030 2.89618 2.37954 2.77424 2.98638 4.58354 3.61644 24 | 0.31308 1.33498 5.17741 2.94235 0.05418 0.00000 * 25 | 1 2.75558 4.37914 4.14325 3.60768 3.56469 3.79941 4.29475 2.76451 3.49028 2.54729 1.29688 3.84073 2.87205 3.76385 3.72203 2.98900 3.08031 2.09197 5.10157 3.90467 41 m - - - 26 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 27 | 0.01453 4.63449 5.35683 0.61958 0.77255 0.48576 0.95510 28 | 2 1.19639 5.15911 2.81385 2.30317 4.49531 3.55142 3.88567 3.93522 2.70950 3.50441 4.30902 3.09227 4.02467 2.69759 3.19136 2.56211 3.02398 3.56585 5.71430 4.34440 42 a - - - 29 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 30 | 0.01449 4.63761 5.35996 0.61958 0.77255 0.48576 0.95510 31 | 3 2.55088 4.29830 4.00597 3.42849 3.41045 3.81667 4.11020 2.64017 3.33620 1.41109 3.14787 3.50630 2.71505 3.50945 3.58391 3.09120 2.71714 2.35156 4.90826 3.70611 43 l - - - 32 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 33 | 0.01446 4.63925 5.36159 0.61958 0.77255 0.48576 0.95510 34 | 4 3.37727 4.69055 5.19425 4.62259 1.11141 4.63131 4.88046 2.22790 4.46933 1.82515 3.13038 4.72406 4.88091 4.54531 4.51653 3.96898 3.60381 1.82312 5.20108 3.93174 44 f - - - 35 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 36 | 0.01446 4.63925 5.36159 0.61958 0.77255 0.48576 0.95510 37 | 5 2.57613 4.86285 3.35996 3.20301 4.64676 3.50134 4.06385 4.19828 3.30624 3.81834 4.70322 3.55149 0.69976 3.59031 3.62345 3.00727 3.31730 3.73281 5.97899 4.66820 45 p - - - 38 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 39 | 0.01446 4.63925 5.36159 0.61958 0.77255 0.48576 0.95510 40 | 6 3.64961 4.88496 5.60761 5.05289 3.34628 5.06774 5.46978 1.47287 4.93159 0.92478 3.21813 5.20853 5.21270 4.94582 4.95586 4.44745 3.87588 1.79343 5.64312 4.59766 46 l - - - 41 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 42 | 0.01442 4.64186 5.36421 0.61958 0.77255 0.48576 0.95510 43 | 7 2.60672 4.50369 3.25589 2.69609 3.86652 3.39908 3.60776 2.86977 2.68149 3.02453 3.64286 2.58087 4.00086 2.21450 3.12212 2.57095 2.16091 2.87218 5.31713 3.60027 47 t - - - 44 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 45 | 0.01442 4.64186 5.36421 0.61958 0.77255 0.48576 0.95510 46 | 8 1.28135 3.42086 4.19270 3.76430 4.59255 1.72378 4.67476 4.00429 3.71454 3.69617 4.51750 3.80036 4.07890 3.97590 4.00411 1.61402 3.05407 3.17786 5.96323 4.78063 48 a - - - 47 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 48 | 0.01442 4.64186 5.36421 0.61958 0.77255 0.48576 0.95510 49 | 9 2.49740 4.79453 3.25361 2.69307 3.99444 3.52729 3.50426 2.70708 2.59469 2.85945 3.70874 1.91863 4.00111 2.94540 2.43035 2.82723 2.97709 2.80702 4.83149 4.02459 49 n - - - 50 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 51 | 0.01442 4.64186 5.36421 0.61958 0.77255 0.48576 0.95510 52 | 10 3.58412 4.91824 4.87499 4.43918 0.69012 4.52165 3.45674 3.36613 4.26992 2.78827 3.99482 4.33884 4.85076 4.33584 4.34038 3.85189 3.70420 2.75999 4.16806 2.28777 50 F - - - 53 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 54 | 0.01442 4.64186 5.36421 0.61958 0.77255 0.48576 0.95510 55 | 11 2.50539 5.20423 2.72757 1.96776 4.52900 3.52480 3.52491 4.00060 2.44172 3.44300 4.25041 2.96962 3.84239 2.30756 2.34012 2.54678 2.97501 2.67785 5.19499 4.25106 51 e - - - 56 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 57 | 0.01442 4.64186 5.36421 0.61958 0.77255 0.48576 0.95510 58 | 12 2.75158 4.78893 2.96217 2.43357 3.89601 1.62337 3.73796 3.59441 2.56355 3.20090 4.01628 3.11234 3.97178 2.94156 2.94348 2.78809 2.53072 3.27393 5.44779 3.45125 52 g - - - 59 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 60 | 0.01442 4.64186 5.36421 0.61958 0.77255 0.48576 0.95510 61 | 13 4.03799 6.08568 0.25363 3.15465 5.61952 4.00444 4.87478 5.43244 4.13298 4.90622 5.95908 3.73017 4.70598 4.15361 4.70551 3.95257 4.40804 5.00376 6.59736 5.44294 53 D - - - 62 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 63 | 0.01442 4.64186 5.36421 0.61958 0.77255 0.48576 0.95510 64 | 14 4.25880 5.39883 5.33478 5.10461 0.47832 4.98650 3.94781 3.70703 4.90242 2.88003 4.29699 4.66669 5.26854 4.75194 4.83087 4.37749 4.48072 3.50073 4.04959 2.11927 54 F - - - 65 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 66 | 0.01442 4.64186 5.36421 0.61958 0.77255 0.48576 0.95510 67 | 15 2.99191 4.24364 4.78695 4.24660 3.74508 3.54268 4.79936 2.16713 4.11132 2.29170 3.62090 4.38836 4.66154 4.35129 4.27495 3.60995 3.34170 0.77003 5.41987 4.21868 55 v - - - 68 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 69 | 0.01440 4.64354 5.36589 0.61958 0.77255 0.48576 0.95510 70 | 16 2.62793 4.35964 3.83234 3.02315 3.47934 3.77838 3.95160 2.61537 3.18764 1.81508 3.28064 3.60318 2.61239 2.94951 3.48404 3.03934 2.98105 1.93836 4.95629 3.74216 56 l - - - 71 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 72 | 0.01440 4.64354 5.36589 0.61958 0.77255 0.48576 0.95510 73 | 17 2.75807 4.75921 3.30568 2.74175 3.94919 3.63647 2.56418 2.63888 2.36325 2.29530 3.58302 3.13890 4.02174 2.11184 3.11373 2.85523 2.98818 2.94991 5.29375 4.00549 57 q - - - 74 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 75 | 0.01440 4.64354 5.36589 0.61958 0.77255 0.48576 0.95510 76 | 18 3.75282 5.14395 5.63311 5.07800 3.39010 5.20160 5.53993 2.47515 4.89209 0.46563 2.95911 5.31766 5.29091 4.89381 4.92292 4.59993 4.10548 2.50216 5.61982 4.63293 58 L - - - 77 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 78 | 0.01440 4.64354 5.36589 0.61958 0.77255 0.48576 0.95510 79 | 19 3.34812 4.70286 5.47478 4.96769 3.95216 4.98212 5.56838 1.53271 4.87637 1.93421 3.64831 5.11363 5.22296 5.08448 5.00893 4.37612 3.61438 0.80832 5.94247 4.75837 59 v - - - 80 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 81 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 82 | 20 1.83973 4.63591 3.42843 2.87627 3.71633 3.65047 3.92743 3.20513 2.84402 2.79752 3.76369 3.32885 1.81860 2.98450 3.24543 2.84440 2.96797 2.76549 5.22551 3.71909 60 p - - - 83 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 84 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 85 | 21 2.98330 4.58712 4.99814 4.51477 3.97634 4.17862 5.15247 1.93784 4.38912 2.66731 3.78059 4.63704 4.86293 4.66048 4.56327 3.72578 3.50118 0.63931 5.76297 4.54642 61 V - - - 86 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 87 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 88 | 22 3.25254 5.80660 0.82958 2.25100 5.14606 3.56559 4.10960 4.66014 3.12044 4.15622 4.99326 2.97700 4.18287 3.27151 3.71832 2.97112 2.45399 4.21931 6.32185 4.81650 62 d - - - 89 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 90 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 91 | 23 2.81258 5.15401 2.12253 2.47496 4.48810 3.52295 3.82468 3.93716 2.62197 3.35129 4.27364 3.00650 3.72931 2.95413 3.10950 2.34560 1.54475 3.49873 5.68024 4.30190 63 t - - - 92 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 93 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 94 | 24 2.28087 5.36772 2.26726 1.58268 4.69610 2.52791 3.75258 4.18361 2.51826 3.66709 4.42203 2.88327 3.97662 2.82101 3.08808 2.80730 2.82834 3.75117 5.80658 4.38262 64 e - - - 95 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 96 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 97 | 25 2.90249 5.54684 1.20904 2.44970 4.53871 3.45186 3.41833 4.36093 2.81033 3.85462 4.64294 1.91345 4.07355 3.06924 3.34877 2.78810 3.29032 3.93385 6.00583 4.55408 65 d - - - 98 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 99 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 100 | 26 2.84578 5.13330 2.29712 2.57750 4.52237 3.53625 3.81584 3.96967 2.73287 3.47444 4.33368 2.99286 3.63642 3.04703 3.21942 2.49284 1.27594 3.58394 5.73871 4.36693 66 t - - - 101 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 102 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 103 | 27 3.49856 4.79250 5.31607 4.76716 3.57472 4.82912 5.25865 2.01229 4.62583 1.99579 1.03924 4.93804 5.06314 4.75014 4.71897 4.19494 3.73820 1.66695 5.58870 4.48977 67 m - - - 104 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 105 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 106 | 28 2.17166 5.25532 1.76870 2.42783 4.58520 3.36616 3.75397 4.06006 2.45651 3.55925 4.31380 2.75281 3.87108 2.86177 2.85148 2.25108 2.79412 3.64068 5.70847 4.30365 68 d - - - 107 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 108 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 109 | 29 2.69388 4.97931 3.10785 1.53400 4.22717 3.57743 3.78333 2.78784 2.57313 3.23945 3.99226 3.10307 3.97087 2.37291 3.01811 2.75243 2.88305 2.83608 5.47985 4.14008 69 e - - - 110 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 111 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 112 | 30 3.53030 4.78402 5.45557 4.99219 3.99465 4.99127 5.68604 1.92587 4.86624 2.25261 3.78221 5.15582 5.27791 5.13767 5.03374 4.42147 3.80333 0.55609 6.06377 4.83006 70 V - - - 113 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 114 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 115 | 31 0.52944 4.16542 4.43298 4.08901 4.53795 3.24221 4.87237 3.30736 3.97728 3.57962 4.49753 3.97876 4.16536 4.24601 4.17950 2.85322 3.12772 3.23873 5.99391 4.82014 71 A - - - 116 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 117 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 118 | 32 1.87506 5.26214 2.35089 1.96232 4.59475 3.34316 3.73415 4.07369 2.47327 3.56202 4.30932 2.99860 3.93401 2.63664 2.40422 2.71937 2.99980 3.53603 5.70164 4.29467 72 a - - - 119 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 120 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 121 | 33 1.76662 4.91436 3.31627 2.76272 4.25163 3.61999 3.89167 3.23024 1.42195 3.24931 4.08929 3.24374 4.04836 3.05570 3.01644 2.80924 3.02361 3.11579 5.51475 4.21425 73 k - - - 122 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 123 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 124 | 34 1.87199 3.32254 4.92418 4.37377 3.71848 4.33715 4.83886 1.83359 4.24210 2.51729 3.62963 4.47766 4.70790 4.44778 4.36659 3.68394 3.34884 1.08188 5.39363 4.19732 74 v - - - 125 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 126 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 127 | 35 0.63688 4.66929 3.76662 3.43729 4.59687 3.45620 4.47085 3.97572 3.20477 3.66651 4.52275 3.66814 4.15183 3.72481 3.04283 2.78893 3.17994 3.52108 5.91377 4.69419 75 A - - - 128 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 129 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 130 | 36 2.63490 4.88495 3.07155 2.50180 4.03958 3.48821 2.48094 3.51311 2.61794 3.10142 3.96091 3.13974 3.98115 2.38155 3.01166 2.72139 2.94699 2.23985 5.39932 2.79746 76 v - - - 131 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 132 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 133 | 37 3.24752 5.33986 3.07776 2.94379 4.32125 3.37220 0.71163 4.39897 3.04068 3.92429 4.83171 2.96706 4.32964 3.49819 3.37345 3.27019 3.58274 4.00894 5.69605 4.20773 77 h - - - 134 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 135 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 136 | 38 1.94546 4.05597 3.87773 3.34527 3.86294 3.45041 4.23430 2.87666 3.29082 2.93333 3.82372 3.63002 4.11932 3.57828 3.61462 1.29576 2.82753 2.34543 5.30839 4.08967 78 s - - - 137 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 138 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 139 | 39 2.75318 4.52417 4.29151 2.67467 3.75902 4.18268 4.55078 2.09697 3.67916 2.52879 3.66429 4.07359 4.54702 3.97108 3.95376 3.48640 3.28647 0.95080 5.38078 4.16305 79 v - - - 140 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 141 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 142 | 40 3.18278 5.48885 2.53518 2.56275 5.13065 0.80436 4.26414 4.64814 3.30183 4.18994 5.04607 2.31338 4.21745 3.45427 3.85123 3.15173 3.54735 4.16689 6.35428 4.90847 80 g - - - 143 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 144 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 145 | 41 2.86721 4.84537 3.44953 2.85117 4.05117 3.72379 3.54763 3.06720 2.22931 2.38915 3.92874 3.31447 4.09914 3.07274 1.48323 2.96396 3.07206 2.74497 5.34922 4.08675 81 r - - - 146 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 147 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 148 | 42 3.19594 5.21906 3.70106 3.07622 3.41405 3.92024 3.17698 3.92027 2.41385 3.44125 4.33686 3.48933 4.29947 3.13925 0.86848 3.16370 3.39714 3.63564 5.32615 3.91230 82 r - - - 149 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 150 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 151 | 43 3.33136 4.73388 4.91993 4.51536 3.89273 4.48768 5.17979 2.19953 4.30300 2.41162 3.79817 4.67072 4.93159 4.30361 4.47537 3.92262 3.63964 0.57685 5.76646 4.49544 83 V - - - 152 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 153 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 154 | 44 1.53159 4.92197 3.18080 2.59769 4.03712 3.59252 3.72040 3.54197 2.43854 3.15240 3.91022 3.13315 2.98719 2.93420 2.44770 2.78673 2.93802 3.18207 5.14501 4.10446 84 a - - - 155 | 2.68622 4.42229 2.77523 2.73115 3.46358 2.40517 3.72498 3.29358 2.67745 2.69359 4.24694 2.90351 2.73744 3.18150 2.89748 2.37891 2.77523 2.98519 4.58481 3.61507 156 | 0.21393 1.88578 3.19697 0.21085 1.66016 0.48576 0.95510 157 | 45 2.11757 5.24766 2.63562 2.04193 4.56760 3.49547 3.75528 4.03837 2.51048 3.54491 4.30625 3.00032 2.00280 2.80322 2.80318 2.66045 3.03158 3.62703 5.70076 4.29858 86 p - - - 158 | 2.68578 4.42231 2.77526 2.73129 3.46360 2.40484 3.72501 3.29360 2.67747 2.69361 4.24696 2.90353 2.73746 3.18152 2.89807 2.37893 2.77526 2.98524 4.58483 3.61509 159 | 0.13584 2.10223 5.33235 0.66939 0.71748 0.44474 1.02441 160 | 46 2.71701 5.26360 3.01249 2.05929 4.60995 3.56486 3.73005 4.07703 1.97199 2.99866 4.30880 3.03739 3.82687 2.17485 2.02730 2.76633 3.02512 3.61591 5.68396 4.30048 89 k - - - 161 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 162 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 163 | 47 2.81058 5.40236 2.65658 2.36567 4.71308 3.49951 3.86373 4.18819 2.60473 3.69563 4.47602 2.25726 1.45499 2.71480 3.15493 2.81489 3.18337 3.77919 5.85655 4.43929 90 p - - - 164 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 165 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 166 | 48 2.55291 5.11355 2.53369 2.46627 4.39954 1.90326 3.50132 3.84635 2.47808 3.31345 4.17264 3.01529 3.94387 2.87064 2.94719 2.32685 2.98984 3.40799 5.58446 3.19508 91 g - - - 167 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 168 | 0.41026 4.64691 1.11800 0.61958 0.77255 0.48576 0.95510 169 | 49 2.64656 4.41055 3.08751 2.49033 4.01586 3.48522 3.34296 3.42233 1.99507 2.99926 3.81459 2.99944 3.75180 2.79409 2.52965 2.69611 2.85262 2.88983 5.29274 2.74857 92 k - - - 170 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 171 | 0.02125 4.25789 4.98024 0.61958 0.77255 0.26768 1.44882 172 | 50 2.65760 4.75473 3.28509 2.15607 3.94956 3.48205 3.74534 2.88775 2.71396 2.98544 3.84501 3.21902 2.22452 3.05198 3.10204 2.69673 2.75571 2.24427 5.29758 4.00590 93 e - - - 173 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 174 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 175 | 51 2.76838 4.28770 4.08075 3.49960 3.34381 3.84740 4.13894 2.49138 2.15102 1.85910 2.61934 3.76654 3.97136 3.64469 3.62591 3.10997 2.89506 1.92014 4.89900 3.60007 94 l - - - 176 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 177 | 0.01798 4.64691 4.80050 0.61958 0.77255 0.48576 0.95510 178 | 52 2.68999 3.02452 3.49922 2.88474 3.73860 3.35936 3.92679 3.10662 2.61446 2.28628 3.67990 3.37015 4.07737 3.10622 1.87820 2.88166 2.99071 2.37573 5.14607 3.89543 95 r - - - 179 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 180 | 0.01440 4.64333 5.36568 0.61958 0.77255 0.48138 0.96214 181 | 53 2.98505 4.49418 4.86101 4.29791 3.52752 4.36731 4.72966 2.24659 4.14373 1.78944 3.47555 4.43734 4.69499 4.34293 4.26617 3.69650 3.37497 0.91944 5.24447 3.34153 96 v - - - 182 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 183 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 184 | 54 2.74747 4.81056 2.52595 2.68336 3.55190 3.61188 3.82423 3.05388 2.56740 2.95890 3.82728 3.18297 3.99925 2.96471 1.77074 2.82378 2.97871 3.00249 4.86755 2.89643 97 r - - - 185 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 186 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 187 | 55 2.67574 4.56556 2.51728 2.58151 3.77605 3.57401 2.65905 3.54577 2.32981 3.04497 4.02507 3.10232 3.96389 2.88381 2.27500 2.77631 2.97600 2.98474 4.78408 2.86508 98 r - - - 188 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 189 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 190 | 56 2.70993 5.25218 2.92652 2.38742 4.59259 3.53458 2.86374 4.06980 2.32336 3.55159 4.29583 2.15102 3.92922 2.05796 2.33141 2.69740 2.99582 3.64072 5.68367 3.85456 99 q - - - 191 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 192 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 193 | 57 2.77439 4.81386 2.96503 2.55396 4.12875 1.57785 3.84125 3.53257 2.65740 3.09777 3.99254 3.14138 4.00507 2.91057 3.05841 2.68983 2.97694 2.39933 5.43008 4.11313 100 g - - - 194 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 195 | 0.39275 4.64691 1.15451 0.61958 0.77255 0.48576 0.95510 196 | 58 2.34613 4.83674 2.81933 2.33607 4.08273 3.05048 3.67779 3.49940 2.45714 2.42408 3.91777 2.89237 3.85676 2.82979 2.94776 2.30897 2.62768 3.13133 5.34880 4.01329 101 s - - - 197 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 198 | 0.02088 4.27504 4.99738 0.61958 0.77255 0.95869 0.48353 199 | 59 2.54278 5.17496 2.01377 2.01009 4.49440 2.96241 3.65453 3.91045 2.32314 3.47101 4.23192 2.86179 3.79539 2.72835 2.91692 2.58259 2.60092 3.55361 5.62324 4.21282 102 e - - - 200 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 201 | 0.02082 4.27798 5.00033 0.61958 0.77255 0.27288 1.43205 202 | 60 2.55038 4.61104 2.85824 2.03884 4.56215 3.45812 3.52165 4.01465 2.34258 3.50861 4.23155 2.99482 2.88140 2.46027 2.07571 2.67285 2.78582 3.53562 5.66731 4.26376 103 e - - - 203 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 204 | 0.01435 4.64691 5.36925 0.61958 0.77255 0.48576 0.95510 205 | 61 2.20193 4.34160 3.32236 2.31590 2.78449 3.64911 3.87581 3.13700 2.55603 2.67007 3.71114 3.22904 3.07049 3.04206 2.97939 2.83393 2.76723 2.44098 5.22694 3.92213 104 a - - - 206 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 207 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 208 | 62 2.99436 4.37837 4.75555 4.15977 2.27295 4.15464 4.42391 2.52150 3.98852 1.08240 3.15293 4.24234 4.48242 3.68460 4.05271 3.46437 3.22221 2.28904 4.88690 2.92102 105 l - - - 209 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 210 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 211 | 63 2.39772 5.10611 2.76729 2.42892 4.45765 3.51323 3.87669 3.89555 2.65867 3.46893 4.27024 3.10377 1.52292 3.01993 3.17705 2.77521 2.38118 3.52498 5.68150 4.31751 106 p - - - 212 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 213 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 214 | 64 2.54120 5.09354 2.78246 2.39997 3.00985 3.10687 3.72752 3.62913 2.50136 3.37256 4.15167 3.04365 3.11662 2.84829 2.04100 2.27607 2.95938 3.42344 5.56553 4.19534 107 r - - - 215 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 216 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 217 | 65 2.69150 5.29669 2.03850 2.19810 4.63062 2.60277 3.11025 4.11460 2.48358 3.59769 4.34408 2.74716 3.94266 2.81383 3.00451 2.19608 2.63897 3.68208 5.73424 4.31997 108 d - - - 218 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 219 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 220 | 66 2.33003 4.44750 3.49962 2.99173 3.63929 3.71447 3.96345 2.95365 2.93386 2.29613 1.98543 3.43169 4.09493 2.52597 3.19939 2.73394 2.80748 2.59377 5.07559 3.83594 109 m - - - 221 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 222 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 223 | 67 2.80527 4.90164 3.28525 2.71673 4.14575 3.53919 3.83700 3.47393 1.93528 3.16229 3.99773 3.20957 4.03261 2.97966 2.71442 2.83585 1.65846 2.51101 5.42099 4.12291 110 t - - - 224 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 225 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 226 | 68 3.11011 4.50616 5.06251 4.49410 3.43993 4.47861 4.88091 1.68886 4.34702 1.52601 3.46881 4.59384 4.03985 4.50717 4.43009 3.81527 3.42437 1.18988 5.34301 4.17828 111 v - - - 227 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 228 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 229 | 69 1.49588 4.53984 3.23947 2.53953 3.83274 2.96705 3.84050 3.47440 2.63165 3.11005 3.94333 3.16104 3.99574 2.95042 3.10639 2.27074 2.87764 3.06179 5.38664 4.07829 112 a - - - 230 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 231 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 232 | 70 2.70012 5.43699 2.20810 1.42252 4.76557 3.35752 3.82757 4.25983 2.59293 3.73609 4.49427 2.99933 4.00100 2.12374 3.14562 2.60177 3.05869 3.82110 5.87182 4.43687 113 e - - - 233 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 234 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 235 | 71 1.79471 4.69016 3.37409 2.82024 3.92469 3.61801 2.77948 3.30577 2.79606 2.77475 3.83530 3.28463 4.03386 3.13031 3.21414 2.06048 2.48470 2.69461 5.29188 4.01386 114 a - - - 236 | 2.68615 4.42228 2.77510 2.73126 3.46357 2.40516 3.72497 3.29357 2.67744 2.69346 4.24693 2.90350 2.73736 3.18149 2.89804 2.37890 2.77517 2.98513 4.58480 3.61506 237 | 0.04126 3.33067 5.37118 0.94118 0.49457 0.48576 0.95510 238 | 72 3.11157 5.51895 2.23291 2.57732 5.12783 0.82432 4.22230 4.63738 3.16938 4.16940 5.01568 2.77714 4.19639 3.40380 3.83109 3.02314 3.52230 4.15834 6.34621 4.88429 119 g - - - 239 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 240 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 241 | 73 3.03366 4.13389 4.95156 4.34804 2.09044 4.23237 4.54783 1.52532 4.15513 1.47388 3.22403 4.37658 4.55013 4.25615 4.17111 3.55203 3.26228 2.20916 4.31766 3.80790 120 l - - - 242 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 243 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 244 | 74 2.39171 5.21134 3.01453 2.27324 4.53832 2.91994 3.71560 3.79068 2.02618 3.25784 4.11983 2.93940 2.88082 2.24137 2.63899 2.71855 2.93797 3.57599 5.65445 4.15066 121 k - - - 245 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 246 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 247 | 75 2.54663 4.81037 3.44453 3.16556 4.53697 3.51625 4.33303 3.93170 3.14155 3.49136 4.47257 3.52163 0.82757 3.07350 3.46798 2.96079 3.23135 3.41698 5.86540 4.59302 122 p - - - 248 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 249 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 250 | 76 2.69164 4.28561 4.15614 3.57714 3.37512 3.86279 3.95279 2.70875 3.44187 1.58867 1.89976 3.81621 4.23716 3.58751 3.64562 3.09341 2.29980 2.52584 4.89554 3.70247 123 l - - - 251 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 252 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 253 | 77 2.99422 5.54171 1.49373 1.59443 4.86709 3.55670 3.88500 4.36497 2.70100 3.83478 4.60622 3.01385 4.04966 2.76815 2.38318 2.92321 3.17595 3.92548 5.96714 4.52401 124 d - - - 254 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 255 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 256 | 78 2.68286 2.95121 4.23462 3.64669 2.97967 3.85446 2.89459 2.66720 3.52275 2.41445 3.33495 3.84457 4.08258 3.73902 3.69547 2.99106 2.28617 2.27260 2.22455 3.28189 125 w - - - 257 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 258 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 259 | 79 3.41893 4.68872 5.39658 4.83641 2.39573 4.78284 5.18559 1.37292 4.69373 1.55608 3.39068 4.92902 5.01824 4.78088 4.73185 4.14166 3.65282 1.41167 5.49811 4.36992 126 i - - - 260 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 261 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 262 | 80 2.59715 5.36559 1.99218 1.39918 4.69349 3.53664 3.80068 4.17856 2.58556 3.66535 4.42290 3.00390 3.98175 2.83882 2.90263 2.75400 2.76831 3.67979 5.80721 4.38553 127 e - - - 263 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 264 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 265 | 81 2.81144 4.54457 5.17165 4.62395 2.64495 4.59858 5.05382 1.64370 4.49239 2.40312 3.60588 4.72447 4.90184 4.67509 4.59057 3.95071 3.49405 0.91257 5.51214 4.31812 128 v - - - 266 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 267 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 268 | 82 2.28307 4.51788 3.41938 2.51366 2.96852 3.07629 3.95101 2.31446 2.94333 2.69451 3.52424 3.40839 4.08603 3.25388 2.48821 2.92303 2.96151 2.51213 5.09280 3.12858 129 a - - - 269 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 270 | 0.01432 4.64883 5.37118 0.61958 0.77255 0.48576 0.95510 271 | 83 4.70251 5.62878 5.54531 5.47594 1.10500 5.18917 3.04633 4.31849 5.25225 3.48774 4.83870 4.71800 5.44012 4.89393 5.04668 4.58975 4.89170 4.25117 2.35885 0.95648 130 y - - - 272 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 273 | 0.01433 4.64814 5.37049 0.61958 0.77255 0.48576 0.95510 274 | 84 2.49331 3.77588 2.55210 2.16389 4.27166 3.52850 3.72695 3.70435 2.50425 3.11817 3.94854 3.03784 3.85772 2.77047 2.36649 2.49473 2.94765 2.47938 5.49098 4.13472 131 e - - - 275 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 276 | 0.12391 4.56118 2.24350 0.61958 0.77255 0.48576 0.95510 277 | 85 2.01135 4.92318 2.49063 2.35667 4.18027 3.16523 3.67526 3.31306 2.43166 3.00975 3.98887 2.93883 3.55019 2.76787 2.93099 2.65907 2.71757 3.08882 5.41309 3.79360 132 a - - - 278 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 279 | 0.06291 4.36594 3.03094 0.61958 0.77255 0.65437 0.73349 280 | 86 2.41268 5.06160 2.82399 1.96453 4.36738 3.30968 3.63311 3.76473 2.35257 3.35090 4.11620 2.85791 2.72938 2.63804 2.82415 2.46198 2.80389 3.22288 5.52094 4.13483 133 e - - - 281 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 282 | 0.17193 4.31023 1.93427 0.61958 0.77255 0.70621 0.68026 283 | 87 2.32567 4.99569 2.81233 2.20055 4.29187 3.17153 3.61729 3.73743 2.15400 3.28087 4.06386 2.89691 2.59039 2.69761 2.74703 2.63068 2.85670 3.33558 5.46657 4.09560 134 k - - - 284 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 285 | 0.04719 4.14559 3.49793 0.61958 0.77255 0.85170 0.55633 286 | 88 2.44697 5.04922 2.14855 2.26775 4.34789 2.70310 3.40805 3.80595 2.36877 3.33686 4.11339 2.85766 3.72250 2.56605 2.87414 2.62407 2.81204 3.26032 5.51423 4.12363 135 d - - - 287 | 2.68334 4.42333 2.77479 2.73225 3.46467 2.40452 3.72590 3.29466 2.67846 2.69372 4.24803 2.90460 2.73502 3.18252 2.89730 2.37979 2.77417 2.98553 4.58591 3.61617 288 | 0.56551 0.83949 * 2.60913 0.07645 0.00000 * 289 | // 290 | -------------------------------------------------------------------------------- /HMMs/individual HMMs/TomA4.hmm: -------------------------------------------------------------------------------- 1 | HMMER3/f [3.2.1 | June 2018] 2 | NAME TomA4 3 | DESC phenol/toluene monooxygenase/hydroxylase (NADH dependent) 4 | LENG 118 5 | ALPH amino 6 | RF no 7 | MM no 8 | CONS yes 9 | CS no 10 | MAP yes 11 | DATE Tue Jul 7 15:29:57 2020 12 | NSEQ 30 13 | EFFN 0.457764 14 | CKSUM 1789604284 15 | TC 200 200; 16 | NC 150 150; 17 | STATS LOCAL MSV -9.9196 0.71384 18 | STATS LOCAL VITERBI -10.4895 0.71384 19 | STATS LOCAL FORWARD -4.0065 0.71384 20 | HMM A C D E F G H I K L M N P Q R S T V W Y 21 | m->m m->i m->d i->m i->i d->m d->d 22 | COMPO 2.50801 4.38723 2.89995 2.86563 3.09589 2.72453 3.64599 2.88972 2.77930 2.39725 3.67910 3.17507 2.86176 3.24420 3.06618 2.68635 2.95079 2.68322 3.97539 3.46520 23 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 24 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.00000 * 25 | 1 2.94404 4.49818 4.01445 3.60584 3.19438 3.80963 4.34860 2.36674 3.37555 1.79437 1.44230 3.88726 4.27041 3.75981 3.58464 3.28954 3.24889 2.36895 5.03058 3.78924 1 m - - - 26 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 27 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 28 | 2 2.29969 4.21939 3.17872 2.99347 4.04387 2.94991 4.10399 3.56228 3.06500 3.28523 4.21441 3.22318 3.68612 3.41700 3.35171 1.14162 2.77746 3.10458 5.41910 4.12735 2 s - - - 29 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 30 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 31 | 3 2.82348 4.33371 4.21150 3.79579 3.46572 3.86135 4.58443 1.88387 3.63864 2.10184 3.38749 4.01206 4.35605 3.98991 3.86845 3.28804 3.15369 1.13827 5.31191 4.03217 3 v - - - 32 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 33 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 34 | 4 2.53922 4.36881 3.30811 2.82067 3.69071 3.39764 3.83027 2.75616 2.36724 2.65456 3.60577 3.21644 3.87739 3.08704 2.98374 2.72512 2.32523 2.03879 5.11840 3.86998 4 v - - - 35 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 36 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 37 | 5 1.22128 4.09907 3.33607 3.10148 4.08213 2.90688 4.15855 3.30989 3.13427 3.15851 4.07533 3.25636 3.65344 3.46013 3.41340 2.21301 2.67561 2.88297 5.49169 4.25334 5 a - - - 38 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 39 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 40 | 6 3.02351 4.50084 4.28270 3.81290 3.12881 4.07441 4.51037 2.10798 3.60406 1.11210 3.04300 4.08957 4.44669 3.92293 3.81142 3.47063 3.30253 1.95680 5.07873 3.83649 6 l - - - 41 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 42 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 43 | 7 2.94286 4.90434 3.11661 2.74485 4.28326 3.43533 3.74230 3.71059 1.08411 3.28309 4.24677 3.17059 3.93837 2.93598 2.42718 2.98727 3.19881 3.42039 5.35178 4.16000 7 k - - - 44 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 45 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 46 | 8 2.59952 4.53058 2.95770 2.72739 3.87857 3.18472 3.48430 3.56960 2.74546 3.16830 4.11266 3.12890 1.43502 3.16915 3.06434 2.71154 2.97131 3.21966 5.22166 3.89324 8 p - - - 47 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 48 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 49 | 9 3.20061 4.70288 3.79020 3.51386 2.29539 3.79222 3.60461 3.21449 3.37232 2.67677 3.89306 3.68369 4.26705 3.68623 3.56257 3.34041 3.48726 3.08355 3.93775 1.02215 9 y - - - 50 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 51 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 52 | 10 2.56112 5.03518 2.30387 2.18269 4.33521 3.30461 3.46857 3.78746 2.14716 3.31323 4.10556 2.57602 3.75560 2.69507 2.52456 2.61301 2.88150 3.40539 5.48339 4.10208 10 k - - - 53 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 54 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 55 | 11 3.21732 4.62891 4.19359 3.90226 1.06700 3.91395 3.86389 2.74552 3.81021 2.12338 3.48084 3.98250 4.37361 3.98737 3.93803 3.48867 3.51861 2.73372 4.12348 2.49492 11 f - - - 56 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 57 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 58 | 12 2.70950 4.47176 3.31322 3.14791 4.14504 3.16116 4.22769 3.68245 3.20248 3.31269 4.36147 3.45767 0.89095 3.59228 3.45133 2.87607 3.14859 3.33152 5.34016 4.26542 12 p - - - 59 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 60 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 61 | 13 1.06212 4.17654 3.42998 3.22032 4.02036 3.00184 4.24615 3.14102 3.23575 3.02408 4.05995 3.37801 3.73801 3.58004 3.48823 2.52733 2.80244 2.80113 5.45081 4.24752 13 a - - - 62 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 63 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 64 | 14 2.93407 5.02541 3.29414 2.69842 4.43358 3.55599 3.56911 3.80100 1.40436 3.28465 4.16281 3.11251 3.94844 2.71406 1.77891 2.94363 3.11995 3.49018 5.36052 4.16994 14 k - - - 65 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 66 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 67 | 15 2.95516 5.07704 0.96628 2.31612 4.44986 3.18653 3.90340 4.03074 2.98151 3.64515 4.62301 2.87064 3.83707 3.14284 3.49288 2.92157 3.29321 3.67359 5.62480 4.32880 15 d - - - 68 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 69 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 70 | 16 2.22357 4.25563 3.56536 3.06782 3.55376 3.44119 3.97847 2.50307 2.90326 2.42391 3.48862 3.39456 3.94092 3.29623 2.94672 2.78688 2.84055 1.72964 5.07455 3.83954 16 v - - - 71 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 72 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 73 | 17 2.89317 4.86798 3.31479 2.79769 4.16672 3.49172 3.65781 3.66570 2.03629 3.16796 4.11832 3.18381 3.94850 2.74512 1.28886 2.94797 3.12952 3.38153 5.27209 4.04172 17 r - - - 74 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 75 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 76 | 18 2.20648 4.78812 2.55589 1.67518 4.22828 3.21583 3.72317 3.51545 2.56573 3.21768 4.10016 2.85470 3.77857 2.90346 2.99655 2.66117 2.84222 3.18197 5.50374 4.15693 18 e - - - 77 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 78 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 79 | 19 2.69705 4.69172 2.69165 2.57406 4.05017 3.16260 3.89589 3.75396 2.79710 3.40471 4.36053 1.21751 3.81308 3.16899 3.15029 2.76575 3.07807 3.37948 5.35993 4.00118 19 n - - - 80 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 81 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 82 | 20 3.21732 4.62891 4.19359 3.90226 1.06700 3.91395 3.86389 2.74552 3.81021 2.12338 3.48084 3.98250 4.37361 3.98737 3.93803 3.48867 3.51861 2.73372 4.12348 2.49492 20 f - - - 83 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 84 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 85 | 21 2.70950 4.47176 3.31322 3.14791 4.14504 3.16116 4.22769 3.68245 3.20248 3.31269 4.36147 3.45767 0.89095 3.59228 3.45133 2.87607 3.14859 3.33152 5.34016 4.26542 21 p - - - 86 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 87 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 88 | 22 1.39148 4.33357 3.09046 2.80701 3.81934 3.11785 3.44511 3.29369 2.79672 2.99801 3.92872 3.14644 3.75640 3.19154 3.11499 2.56811 2.81011 2.95145 5.22810 3.90387 22 a - - - 89 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 90 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 91 | 23 2.70950 4.47176 3.31322 3.14791 4.14504 3.16116 4.22769 3.68245 3.20248 3.31269 4.36147 3.45767 0.89095 3.59228 3.45133 2.87607 3.14859 3.33152 5.34016 4.26542 23 p - - - 92 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 93 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 94 | 24 3.11893 4.59121 4.13659 3.77679 3.12406 3.94005 4.44284 2.32692 3.54484 0.91670 3.15818 4.05539 4.38139 3.92104 3.72608 3.50781 3.41487 2.35563 4.99093 3.70651 24 l - - - 95 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 96 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 97 | 25 3.11893 4.59121 4.13659 3.77679 3.12406 3.94005 4.44284 2.32692 3.54484 0.91670 3.15818 4.05539 4.38139 3.92104 3.72608 3.50781 3.41487 2.35563 4.99093 3.70651 25 l - - - 98 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 99 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 100 | 26 3.32251 4.66736 4.30598 3.92624 1.35200 4.14226 3.45171 3.03463 3.79361 2.41548 3.65802 3.86950 4.47340 3.87327 3.91045 3.49734 3.55309 2.95750 3.64558 1.51753 26 f - - - 101 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 102 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 103 | 27 3.03699 4.43657 4.41479 3.95401 3.28213 4.19473 4.65738 1.21808 3.75875 1.76880 3.19004 4.21803 4.54872 4.09005 3.96558 3.60170 3.30966 1.79217 5.21909 3.95511 27 i - - - 104 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 105 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 106 | 28 2.62542 4.40354 3.29243 3.18795 4.32980 0.78159 4.30978 3.92186 3.36470 3.58001 4.55587 3.45685 3.79362 3.69154 3.60390 2.79648 3.10413 3.45656 5.43315 4.43076 28 g - - - 107 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 108 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 109 | 29 3.28253 4.66864 4.04191 3.74024 2.63472 3.69415 3.86108 3.30517 3.46333 2.70552 3.94044 3.89602 4.20926 3.85269 3.59731 3.48651 3.58138 3.19460 0.95416 2.63861 29 w - - - 110 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 111 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 112 | 30 2.84760 5.28685 1.94621 1.36202 4.58039 3.17876 3.70262 4.05913 2.67287 3.61383 4.48008 2.67194 3.78362 2.87544 3.21542 2.76207 3.13376 3.67122 5.77509 4.32732 30 e - - - 113 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 114 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 115 | 31 2.88516 5.30380 1.25651 1.96382 4.60807 3.15624 3.74323 4.10002 2.77430 3.67316 4.56675 2.66767 3.79028 2.92968 3.34224 2.79481 3.18852 3.71249 5.81900 4.36554 31 d - - - 116 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 117 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 118 | 32 2.96044 4.78291 3.09509 2.85219 3.26283 3.42071 1.21364 3.65823 2.69619 3.15614 4.19690 3.26266 3.97168 3.21813 2.96364 3.03157 3.26289 3.39403 4.72824 3.21471 32 h - - - 119 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 120 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 121 | 33 3.11893 4.59121 4.13659 3.77679 3.12406 3.94005 4.44284 2.32692 3.54484 0.91670 3.15818 4.05539 4.38139 3.92104 3.72608 3.50781 3.41487 2.35563 4.99093 3.70651 33 l - - - 122 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 123 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 124 | 34 3.05859 4.52228 4.29331 3.76424 3.05880 4.14544 4.45231 2.18336 3.55120 1.35362 1.85914 4.07442 4.44679 3.84773 3.76044 3.49647 3.30284 2.23842 5.01497 3.82695 34 l - - - 125 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 126 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 127 | 35 3.23256 4.63665 4.21146 3.85242 1.20089 4.06302 3.65196 2.78167 3.72864 2.14049 3.45933 3.90004 4.43581 3.87838 3.87238 3.46982 3.49017 2.76061 3.88778 2.14740 35 f - - - 128 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 129 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 130 | 36 1.83474 2.41837 3.62463 3.19675 3.83455 2.47809 4.08609 3.17261 3.13655 2.92016 3.78757 3.31349 3.07287 3.42125 3.41840 2.37600 2.60818 2.77745 5.24994 4.05393 36 a - - - 131 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 132 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 133 | 37 1.67633 3.22601 3.63721 3.22124 3.95014 2.90861 4.12919 3.24145 3.15498 3.02712 3.89162 3.31004 3.63028 3.44550 3.43766 1.72267 2.51872 2.81464 5.35506 4.15879 37 a - - - 134 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 135 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 136 | 38 2.70950 4.47176 3.31322 3.14791 4.14504 3.16116 4.22769 3.68245 3.20248 3.31269 4.36147 3.45767 0.89095 3.59228 3.45133 2.87607 3.14859 3.33152 5.34016 4.26542 38 p - - - 137 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 138 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 139 | 39 2.88168 4.34400 4.31262 3.85672 3.45364 3.99566 4.63727 1.77152 3.70713 2.04762 3.33895 4.09408 4.43502 4.03913 3.94100 3.39838 3.18730 1.15391 5.32883 4.07082 39 v - - - 140 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 141 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 142 | 40 1.23467 3.29433 3.77960 3.40978 3.90903 2.96223 4.25892 2.94807 3.30455 2.90385 3.87529 3.43343 3.69640 3.61066 3.54320 2.41802 2.66288 2.60626 5.38436 4.18696 40 a - - - 143 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 144 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 145 | 41 3.11667 4.57082 4.33900 3.83813 3.04464 4.18636 4.50212 2.16126 3.58830 1.01888 2.76451 4.13809 4.49711 3.91021 3.78682 3.56706 3.37027 2.21991 5.02590 3.79733 41 l - - - 146 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 147 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 148 | 42 2.70950 4.47176 3.31322 3.14791 4.14504 3.16116 4.22769 3.68245 3.20248 3.31269 4.36147 3.45767 0.89095 3.59228 3.45133 2.87607 3.14859 3.33152 5.34016 4.26542 42 p - - - 149 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 150 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 151 | 43 3.11667 4.57082 4.33900 3.83813 3.04464 4.18636 4.50212 2.16126 3.58830 1.01888 2.76451 4.13809 4.49711 3.91021 3.78682 3.56706 3.37027 2.21991 5.02590 3.79733 43 l - - - 152 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 153 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 154 | 44 2.70950 4.47176 3.31322 3.14791 4.14504 3.16116 4.22769 3.68245 3.20248 3.31269 4.36147 3.45767 0.89095 3.59228 3.45133 2.87607 3.14859 3.33152 5.34016 4.26542 44 p - - - 155 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 156 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 157 | 45 1.82931 4.18865 3.17240 2.85310 4.11182 2.95238 3.98231 3.49210 2.90878 3.18807 4.03193 3.12867 2.27697 3.22714 3.25896 2.02350 2.66827 3.03005 5.45231 4.20630 45 a - - - 158 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 159 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 160 | 46 2.88610 5.28179 1.23119 2.00010 4.59202 3.15675 3.75286 4.08481 2.78679 3.66648 4.56639 2.67868 3.79285 2.94260 3.35093 2.80039 3.19264 3.70067 5.80555 4.36072 46 d - - - 161 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 162 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 163 | 47 2.57193 4.29148 3.61287 3.12891 3.46799 3.47317 4.03457 2.51456 2.98429 2.26140 2.44270 3.44992 3.97572 3.35671 3.27853 2.82965 2.02311 2.35707 5.07316 3.84399 47 t - - - 164 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 165 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 166 | 48 2.58347 4.41601 3.30900 2.93520 3.60627 3.32689 3.94340 2.93438 2.82729 2.14383 3.68387 3.29440 1.85847 3.24457 3.13425 2.76131 2.92700 2.73059 5.11342 3.81017 48 p - - - 167 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 168 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 169 | 49 3.21732 4.62891 4.19359 3.90226 1.06700 3.91395 3.86389 2.74552 3.81021 2.12338 3.48084 3.98250 4.37361 3.98737 3.93803 3.48867 3.51861 2.73372 4.12348 2.49492 49 f - - - 170 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 171 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 172 | 50 2.62542 4.40354 3.29243 3.18795 4.32980 0.78159 4.30978 3.92186 3.36470 3.58001 4.55587 3.45685 3.79362 3.69154 3.60390 2.79648 3.10413 3.45656 5.43315 4.43076 50 g - - - 173 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 174 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 175 | 51 1.32805 4.33274 2.73265 2.74382 4.06159 3.05433 3.98214 3.28973 2.94259 3.11886 4.04253 3.10305 3.72817 3.23991 3.31007 2.53431 2.80578 2.92920 5.43871 4.16433 51 a - - - 176 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 177 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 178 | 52 3.11893 4.59121 4.13659 3.77679 3.12406 3.94005 4.44284 2.32692 3.54484 0.91670 3.15818 4.05539 4.38139 3.92104 3.72608 3.50781 3.41487 2.35563 4.99093 3.70651 52 l - - - 179 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 180 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 181 | 53 1.81647 3.36310 3.50154 3.00927 3.72070 2.70440 3.94704 3.05018 2.87953 2.79370 3.66536 3.25431 3.70961 3.25514 3.27856 2.31853 2.54026 2.52397 5.13500 3.91657 53 a - - - 182 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 183 | 0.04300 3.83966 3.88303 0.61958 0.77255 0.48576 0.95510 184 | 54 2.58893 4.77551 2.76122 2.33017 4.12175 3.31050 3.64766 3.49345 2.36279 3.11060 3.97311 2.91218 3.79877 2.06659 2.73221 2.67786 2.42978 3.17312 5.35752 4.04750 54 q - - - 185 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 186 | 0.03280 3.82946 4.55180 0.61958 0.77255 0.48022 0.96403 187 | 55 1.72301 4.50813 2.87881 2.55441 4.01938 2.92649 3.75666 3.39874 2.45341 3.05760 3.91797 2.99332 3.75787 2.74236 2.93080 2.59199 2.82190 3.05254 5.32303 4.03988 55 a - - - 188 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 189 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 190 | 56 2.78232 4.33453 4.07949 3.74209 3.52665 3.68943 4.54965 2.05362 3.60935 2.21973 3.49728 3.93704 4.25212 3.97174 3.82492 3.19129 3.14489 1.06737 5.30538 4.03474 56 v - - - 191 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 192 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 193 | 57 3.11893 4.59121 4.13659 3.77679 3.12406 3.94005 4.44284 2.32692 3.54484 0.91670 3.15818 4.05539 4.38139 3.92104 3.72608 3.50781 3.41487 2.35563 4.99093 3.70651 57 l - - - 194 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 195 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 196 | 58 2.70950 4.47176 3.31322 3.14791 4.14504 3.16116 4.22769 3.68245 3.20248 3.31269 4.36147 3.45767 0.89095 3.59228 3.45133 2.87607 3.14859 3.33152 5.34016 4.26542 58 p - - - 197 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 198 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 199 | 59 2.49761 4.74793 2.02374 2.30471 4.37425 1.81889 3.79617 3.82242 2.77105 3.44592 4.29858 2.81269 3.73040 2.99150 3.26294 2.60993 2.94154 3.39527 5.63803 4.27040 59 g - - - 200 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 201 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 202 | 60 2.68708 4.25499 3.98711 3.48792 3.52580 3.72349 4.33627 1.92682 3.37374 2.24332 3.40285 3.76392 4.19451 3.70036 3.65085 3.08332 2.43018 1.44255 5.22764 4.00532 60 v - - - 203 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 204 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 205 | 61 3.25011 4.68956 4.06079 3.69174 1.95106 4.01733 3.47374 3.08011 3.55934 2.50780 3.73566 3.75536 4.39361 3.74366 3.73729 3.39686 3.49822 2.97831 3.72160 1.14886 61 y - - - 206 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 207 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 208 | 62 2.62542 4.40354 3.29243 3.18795 4.32980 0.78159 4.30978 3.92186 3.36470 3.58001 4.55587 3.45685 3.79362 3.69154 3.60390 2.79648 3.10413 3.45656 5.43315 4.43076 62 g - - - 209 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 210 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 211 | 63 2.26729 4.30796 3.33857 2.67018 3.41515 3.48774 3.75290 2.74649 2.72654 2.48680 3.24734 3.21379 3.88470 3.06534 3.08050 2.74950 2.78650 2.40538 4.87243 2.76682 63 a - - - 212 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 213 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 214 | 64 2.96044 4.78291 3.09509 2.85219 3.26283 3.42071 1.21364 3.65823 2.69619 3.15614 4.19690 3.26266 3.97168 3.21813 2.96364 3.03157 3.26289 3.39403 4.72824 3.21471 64 h - - - 215 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 216 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 217 | 65 2.70950 4.47176 3.31322 3.14791 4.14504 3.16116 4.22769 3.68245 3.20248 3.31269 4.36147 3.45767 0.89095 3.59228 3.45133 2.87607 3.14859 3.33152 5.34016 4.26542 65 p - - - 218 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 219 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 220 | 66 2.95516 5.07704 0.96628 2.31612 4.44986 3.18653 3.90340 4.03074 2.98151 3.64515 4.62301 2.87064 3.83707 3.14284 3.49288 2.92157 3.29321 3.67359 5.62480 4.32880 66 d - - - 221 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 222 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 223 | 67 3.21732 4.62891 4.19359 3.90226 1.06700 3.91395 3.86389 2.74552 3.81021 2.12338 3.48084 3.98250 4.37361 3.98737 3.93803 3.48867 3.51861 2.73372 4.12348 2.49492 67 f - - - 224 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 225 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 226 | 68 1.78077 4.56175 2.47900 2.38780 4.12312 3.02662 3.76136 3.51951 2.67354 3.17095 4.01221 2.90544 3.72404 2.95818 3.12159 2.30196 2.81782 3.14018 5.42762 4.10695 68 a - - - 227 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 228 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 229 | 69 2.94207 5.02748 3.32395 2.71193 4.43870 3.56587 3.56646 3.80245 1.51092 3.28353 4.16204 3.12138 3.95362 2.71099 1.62265 2.95234 3.12476 3.49316 5.35728 4.17181 69 k - - - 230 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 231 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 232 | 70 3.00562 4.43411 4.28810 3.90305 3.35260 4.03032 4.63760 1.11951 3.73051 1.94592 3.29365 4.15302 4.46512 4.08248 3.93087 3.52285 3.30556 1.84640 5.23630 3.97142 70 i - - - 233 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 234 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 235 | 71 2.82622 5.19223 1.27536 2.11754 4.51148 3.13741 3.75073 4.08180 2.78516 3.65887 4.54512 2.48315 3.77906 2.94499 3.34302 2.75880 3.14751 3.67596 5.76261 4.29467 71 d - - - 236 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 237 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 238 | 72 3.28253 4.66864 4.04191 3.74024 2.63472 3.69415 3.86108 3.30517 3.46333 2.70552 3.94044 3.89602 4.20926 3.85269 3.59731 3.48651 3.58138 3.19460 0.95416 2.63861 72 w - - - 239 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 240 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 241 | 73 2.40973 4.79233 2.11745 2.27740 4.31272 3.05913 3.70657 3.76238 2.61635 3.34993 4.17301 2.61933 3.72728 2.87677 3.10992 1.96819 2.88740 3.35323 5.56089 4.18486 73 s - - - 242 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 243 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 244 | 74 2.44127 4.53868 2.89032 2.19979 4.07330 3.36912 3.38904 3.48737 2.13865 3.07188 3.88783 2.89539 3.77442 2.50148 2.71190 2.61286 2.67326 3.15761 5.29168 3.96530 74 k - - - 245 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 246 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 247 | 75 2.50388 4.26044 3.99037 3.62574 3.60191 3.59009 4.48667 2.05384 3.51192 2.28869 3.51022 3.81619 4.17071 3.86272 3.75124 3.03316 3.02457 1.19177 5.36011 4.10925 75 v - - - 248 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 249 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 250 | 76 2.79704 5.10939 2.46125 1.76052 4.39146 3.28771 3.64035 3.84860 2.37224 3.38125 4.24591 2.79570 3.81328 2.03657 2.76526 2.75628 3.04999 3.49901 5.55009 4.18449 76 e - - - 251 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 252 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 253 | 77 3.28253 4.66864 4.04191 3.74024 2.63472 3.69415 3.86108 3.30517 3.46333 2.70552 3.94044 3.89602 4.20926 3.85269 3.59731 3.48651 3.58138 3.19460 0.95416 2.63861 77 w - - - 254 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 255 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 256 | 78 2.87331 4.41266 4.00499 3.57194 1.59083 3.81161 3.95860 2.46463 3.45301 1.95125 3.26663 3.77475 4.24355 3.70810 3.66806 3.18523 2.88796 2.40067 4.41881 2.88159 78 f - - - 257 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 258 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 259 | 79 2.90485 4.95153 3.12465 2.67793 4.32840 3.47288 3.64108 3.73692 1.22721 3.26851 4.18318 3.10413 3.93056 2.80825 2.20588 2.93086 3.13163 3.43291 5.36029 4.14329 79 k - - - 260 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 261 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 262 | 80 2.29969 4.21939 3.17872 2.99347 4.04387 2.94991 4.10399 3.56228 3.06500 3.28523 4.21441 3.22318 3.68612 3.41700 3.35171 1.14162 2.77746 3.10458 5.41910 4.12735 80 s - - - 263 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 264 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 265 | 81 2.62542 4.40354 3.29243 3.18795 4.32980 0.78159 4.30978 3.92186 3.36470 3.58001 4.55587 3.45685 3.79362 3.69154 3.60390 2.79648 3.10413 3.45656 5.43315 4.43076 81 g - - - 266 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 267 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 268 | 82 2.81114 5.04580 2.64435 2.22821 4.35269 3.35777 3.61596 3.77434 2.13917 3.30970 4.17287 2.87514 3.84510 1.76908 2.54711 2.79115 3.04571 3.44181 5.46717 4.15379 82 q - - - 269 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 270 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 271 | 83 2.32429 4.44621 2.87967 2.61312 4.06747 3.11297 3.83085 3.47733 2.65784 3.13036 4.01453 3.01777 1.89245 2.85198 3.01186 2.49820 2.81567 3.09897 5.39152 4.09527 83 p - - - 272 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 273 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 274 | 84 3.28253 4.66864 4.04191 3.74024 2.63472 3.69415 3.86108 3.30517 3.46333 2.70552 3.94044 3.89602 4.20926 3.85269 3.59731 3.48651 3.58138 3.19460 0.95416 2.63861 84 w - - - 275 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 276 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 277 | 85 2.57312 4.64471 3.01003 2.48435 3.88854 3.38866 3.34273 3.28621 2.18258 2.91416 3.53529 2.97302 3.79689 2.73910 2.75224 2.37191 2.44889 2.99016 5.17443 3.87901 85 k - - - 278 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 279 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 280 | 86 2.70950 4.47176 3.31322 3.14791 4.14504 3.16116 4.22769 3.68245 3.20248 3.31269 4.36147 3.45767 0.89095 3.59228 3.45133 2.87607 3.14859 3.33152 5.34016 4.26542 86 p - - - 281 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 282 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 283 | 87 2.88943 5.22944 1.17782 2.07307 4.55390 3.15900 3.77801 4.05365 2.81900 3.65265 4.56797 2.70898 3.79945 2.97610 3.37359 2.81530 3.20365 3.67656 5.77037 4.34864 87 d - - - 284 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 285 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 286 | 88 1.92621 4.23402 3.16193 2.90513 4.08642 2.99336 4.03874 3.38886 2.95563 3.13145 4.05641 3.18086 1.73200 3.30398 3.27531 2.46716 2.74903 2.98581 5.45139 4.21322 88 p - - - 287 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 288 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 289 | 89 1.34205 4.08231 3.34692 3.07273 4.11445 2.89104 4.12864 3.37806 3.10141 3.18311 4.05931 3.23235 3.63132 3.41484 3.39621 2.02557 2.54435 2.92195 5.49782 4.27837 89 a - - - 290 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 291 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 292 | 90 2.89344 4.96743 3.01570 2.62176 4.30624 3.45079 3.63969 3.73400 1.26078 3.26116 4.18288 3.06296 3.92056 2.72134 2.30441 2.91201 3.12530 3.43154 5.37260 4.12759 90 k - - - 293 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 294 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 295 | 91 2.21370 4.15476 3.21183 2.96452 4.12094 2.91694 4.07244 3.47803 3.00146 3.23057 4.11430 3.18290 3.64736 3.34568 3.30638 1.34205 2.39838 3.01350 5.49196 4.23335 91 s - - - 296 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 297 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 298 | 92 3.11893 4.59121 4.13659 3.77679 3.12406 3.94005 4.44284 2.32692 3.54484 0.91670 3.15818 4.05539 4.38139 3.92104 3.72608 3.50781 3.41487 2.35563 4.99093 3.70651 92 l - - - 299 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 300 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 301 | 93 1.93485 4.77820 2.64576 2.10606 4.12359 3.27318 3.67399 3.50308 2.47072 3.13288 3.99550 2.87660 3.78859 2.57347 2.87750 2.67082 2.91297 3.17894 5.38959 4.06244 93 a - - - 302 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 303 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 304 | 94 2.34251 5.11594 1.90459 1.86195 4.44859 2.93742 3.65589 3.90451 2.57998 3.46024 4.28596 2.70113 3.75634 2.81344 3.11377 2.66885 2.99663 3.51444 5.65828 4.23047 94 e - - - 305 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 306 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 307 | 95 2.69705 4.69172 2.69165 2.57406 4.05017 3.16260 3.89589 3.75396 2.79710 3.40471 4.36053 1.21751 3.81308 3.16899 3.15029 2.76575 3.07807 3.37948 5.35993 4.00118 95 n - - - 308 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 309 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 310 | 96 2.62542 4.40354 3.29243 3.18795 4.32980 0.78159 4.30978 3.92186 3.36470 3.58001 4.55587 3.45685 3.79362 3.69154 3.60390 2.79648 3.10413 3.45656 5.43315 4.43076 96 g - - - 311 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 312 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 313 | 97 3.11893 4.59121 4.13659 3.77679 3.12406 3.94005 4.44284 2.32692 3.54484 0.91670 3.15818 4.05539 4.38139 3.92104 3.72608 3.50781 3.41487 2.35563 4.99093 3.70651 97 l - - - 314 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 315 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 316 | 98 2.53116 4.65828 2.97449 2.47717 3.96550 2.94662 3.62314 3.26906 2.08492 2.97832 3.81822 2.96240 3.78660 2.66031 2.74911 2.62750 2.44785 2.98342 5.23211 3.93532 98 k - - - 317 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 318 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 319 | 99 2.96044 4.78291 3.09509 2.85219 3.26283 3.42071 1.21364 3.65823 2.69619 3.15614 4.19690 3.26266 3.97168 3.21813 2.96364 3.03157 3.26289 3.39403 4.72824 3.21471 99 h - - - 320 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 321 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 322 | 100 2.89274 5.00497 2.99233 2.58454 4.34671 3.46211 3.61183 3.76687 1.31973 3.27609 4.17692 3.03500 3.91539 2.58656 2.27678 2.89935 3.11168 3.45733 5.38593 4.13996 100 k - - - 323 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 324 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 325 | 101 2.58178 5.02360 1.28105 2.19966 4.43807 3.13897 3.79197 3.85392 2.81479 3.52207 4.44410 2.74988 3.78143 2.99162 3.34752 2.74064 3.10456 3.48476 5.71431 4.29328 101 d - - - 326 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 327 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 328 | 102 2.20028 4.25390 3.92061 3.44519 3.52551 3.64001 4.30523 2.09805 3.33266 2.11302 3.41860 3.71155 4.14299 3.66454 3.60898 3.01359 2.97196 1.49238 5.21968 3.98957 102 v - - - 329 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 330 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 331 | 103 3.00562 4.43411 4.28810 3.90305 3.35260 4.03032 4.63760 1.11951 3.73051 1.94592 3.29365 4.15302 4.46512 4.08248 3.93087 3.52285 3.30556 1.84640 5.23630 3.97142 103 i - - - 332 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 333 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 334 | 104 2.72896 4.16528 3.46975 2.90617 4.00566 3.40094 3.75841 3.41979 2.24929 3.03442 3.99596 3.25891 3.90160 2.97138 1.31053 2.84241 3.02025 3.13702 5.22070 3.99665 104 r - - - 335 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 336 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 337 | 105 3.21732 4.62891 4.19359 3.90226 1.06700 3.91395 3.86389 2.74552 3.81021 2.12338 3.48084 3.98250 4.37361 3.98737 3.93803 3.48867 3.51861 2.73372 4.12348 2.49492 105 f - - - 338 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 339 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 340 | 106 2.96932 4.80980 3.45672 2.97529 4.15609 3.46298 3.80199 3.69593 2.22631 3.21787 4.21937 3.33730 3.96758 3.02435 1.02974 3.05536 3.23780 3.42142 5.25272 4.09105 106 r - - - 341 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 342 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 343 | 107 2.39595 4.24079 3.39984 3.15090 3.94074 3.08100 4.17062 3.06391 3.09322 2.92854 3.98158 3.36521 3.78235 3.48982 3.35319 2.59690 1.22878 2.76239 5.38146 4.15752 107 t - - - 344 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 345 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 346 | 108 2.35872 4.29866 3.05675 2.85012 4.07150 3.00644 4.01332 3.53570 2.91752 3.23137 4.15038 3.15374 1.50078 3.28978 3.22923 2.34358 2.80448 3.10983 5.42127 4.14246 108 p - - - 347 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 348 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 349 | 109 2.62542 4.40354 3.29243 3.18795 4.32980 0.78159 4.30978 3.92186 3.36470 3.58001 4.55587 3.45685 3.79362 3.69154 3.60390 2.79648 3.10413 3.45656 5.43315 4.43076 109 g - - - 350 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 351 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 352 | 110 3.11893 4.59121 4.13659 3.77679 3.12406 3.94005 4.44284 2.32692 3.54484 0.91670 3.15818 4.05539 4.38139 3.92104 3.72608 3.50781 3.41487 2.35563 4.99093 3.70651 110 l - - - 353 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 354 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 355 | 111 2.43416 4.31994 3.21350 2.75997 3.72836 3.25673 3.81280 2.66688 2.70687 2.78032 3.67297 2.82888 3.78794 3.07116 3.06437 2.47373 2.00551 2.70767 5.12735 3.86348 111 t - - - 356 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 357 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 358 | 112 2.62542 4.40354 3.29243 3.18795 4.32980 0.78159 4.30978 3.92186 3.36470 3.58001 4.55587 3.45685 3.79362 3.69154 3.60390 2.79648 3.10413 3.45656 5.43315 4.43076 112 g - - - 359 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 360 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 361 | 113 3.05416 4.42200 4.53854 4.01953 3.28138 4.30263 4.72339 1.32504 3.86317 1.62311 3.12327 4.29347 4.59681 4.13602 4.07194 3.66583 3.30822 1.70065 5.25368 4.05345 113 i - - - 362 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 363 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 364 | 114 2.50165 4.87979 2.64581 2.27229 4.19343 3.05040 3.47437 3.62525 2.39091 3.19956 4.02120 2.59251 3.76952 2.22312 2.82553 2.46205 2.88459 3.27531 5.40903 4.05997 114 q - - - 365 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 366 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 367 | 115 2.62542 4.40354 3.29243 3.18795 4.32980 0.78159 4.30978 3.92186 3.36470 3.58001 4.55587 3.45685 3.79362 3.69154 3.60390 2.79648 3.10413 3.45656 5.43315 4.43076 115 g - - - 368 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 369 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 370 | 116 2.21725 4.15840 3.20139 2.96382 4.11964 2.91615 4.07578 3.48595 3.00567 3.23762 4.12546 3.18261 3.64884 3.35129 3.30860 1.31646 2.45832 3.02049 5.49320 4.22945 116 s - - - 371 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 372 | 0.03246 3.83966 4.56200 0.61958 0.77255 0.48576 0.95510 373 | 117 2.69251 2.61658 4.02276 3.48621 2.18661 3.72018 3.80536 2.52437 3.36234 2.20189 3.25059 3.66130 4.10638 3.57794 3.55559 3.03112 2.94093 2.36719 4.29547 2.51682 117 f - - - 374 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 375 | 0.04342 3.83966 3.86351 0.61958 0.77255 0.48576 0.95510 376 | 118 2.36347 4.37904 2.83647 2.63091 4.12782 3.00868 3.89119 3.64904 2.78618 3.30697 4.16174 2.48921 3.68577 3.12795 3.15205 1.51885 2.78395 3.19011 5.45730 4.12681 118 s - - - 377 | 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 378 | 0.02221 3.81844 * 0.61958 0.77255 0.00000 * 379 | // 380 | --------------------------------------------------------------------------------