Mercurial > repos > iuc > dada2_dada

annotate test-data/gentest.R @ 2:4181dc15f538 draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit f2a33fe115fef9d711112b53136cf7619f1b19be"
author iuc
date Mon, 16 Mar 2020 11:28:01 +0000
parents 93a3cbe14318
children 724307021d1e
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93a3cbe14318 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit f8b6b6e72914ad6bcca8423dfa03f59bde80992e"
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diff changeset
1 library(dada2, quietly=T)
93a3cbe14318 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit f8b6b6e72914ad6bcca8423dfa03f59bde80992e"
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2 library(ggplot2, quietly=T)
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3
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4181dc15f538 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit f2a33fe115fef9d711112b53136cf7619f1b19be"
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4 sample.names <- c('F3D0_S188_L001', 'F3D141_S207_L001')
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5 fwd <- c('F3D0_S188_L001_R1_001.fastq.gz', 'F3D141_S207_L001_R1_001.fastq.gz')
4181dc15f538 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit f2a33fe115fef9d711112b53136cf7619f1b19be"
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6 rev <- c('F3D0_S188_L001_R2_001.fastq.gz', 'F3D141_S207_L001_R2_001.fastq.gz')
4181dc15f538 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit f2a33fe115fef9d711112b53136cf7619f1b19be"
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4181dc15f538 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit f2a33fe115fef9d711112b53136cf7619f1b19be"
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8 filt.fwd <- c('filterAndTrim_F3D0_R1.fq.gz', 'filterAndTrim_F3D141_R1.fq.gz')
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9 filt.rev <- c('filterAndTrim_F3D0_R2.fq.gz', 'filterAndTrim_F3D141_R2.fq.gz')
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4181dc15f538 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit f2a33fe115fef9d711112b53136cf7619f1b19be"
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11 print("filterAndTrim")
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12
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4181dc15f538 "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit f2a33fe115fef9d711112b53136cf7619f1b19be"
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13 for(i in 1:length(fwd)){
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14 ftout <- filterAndTrim(fwd[i], filt.fwd[i], rev[i], filt.rev[i])
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15 b <- paste(strsplit(fwd[i], ".", fixed=T)[[1]][1], "tab", sep=".")
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16 write.table(ftout, b, quote=F, sep="\t", col.names=NA)
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17 }
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19 # In the test only the 1st data set is used
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20 t <- data.frame()
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21 t <- rbind(t, ftout[1,])
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22 colnames(t) <- colnames(ftout)
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23 rownames(t) <- rownames(ftout)[1]
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24 write.table(t, "filterAndTrim.tab", quote=F, sep="\t", col.names=NA)
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26 names(fwd) <- sample.names
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27 names(rev) <- sample.names
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28 names(filt.fwd) <- sample.names
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29 names(filt.rev) <- sample.names
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31 # Plot quality profile (just for one file, Galaxy compares with sim_size)
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32 print("plots")
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33 qp <- plotQualityProfile(fwd)
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34 ggsave('qualityProfile_fwd.pdf', qp, width = 20,height = 15,units = c("cm"))
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35 qp <- plotQualityProfile(rev)
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36 ggsave('qualityProfile_rev.pdf', qp, width = 20,height = 15,units = c("cm"))
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37 qp <- plotQualityProfile(fwd[1])
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38 ggsave('qualityProfile.pdf', qp, width = 20,height = 15,units = c("cm"))
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40 # Plot complexity (just for one file, Galaxy compares with sim_size)
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42 cp <- plotComplexity(fwd)
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43 ggsave('complexity_fwd.pdf', cp, width = 20,height = 15,units = c("cm"))
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44 cp <- plotComplexity(rev)
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45 ggsave('complexity_rev.pdf', cp, width = 20,height = 15,units = c("cm"))
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46 cp <- plotComplexity(fwd[1])
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47 ggsave('complexity.pdf', cp, width = 20,height = 15,units = c("cm"))
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49
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50 # learn Errors
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51 print("learnErrors")
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52 err.fwd <- learnErrors(filt.fwd)
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53 saveRDS(err.fwd, file='learnErrors_R1.Rdata')
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54 plot <- plotErrors(err.fwd)
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55 ggsave('learnErrors_R1.pdf', plot, width = 20,height = 15,units = c("cm"))
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56
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57 err.rev <- learnErrors(filt.rev)
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58 saveRDS(err.rev, file='learnErrors_R2.Rdata')
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59 plot <- plotErrors(err.rev)
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60 ggsave('learnErrors.pdf', plot, width = 20,height = 15,units = c("cm"))
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61
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62 # dada
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63 print("dada")
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64 dada.fwd <- dada(filt.fwd, err.fwd)
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65 dada.rev <- dada(filt.rev, err.rev)
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66 for( id in sample.names ){
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67 saveRDS(dada.fwd[[id]], file=paste("dada_", id,"_R1.Rdata", sep=""))
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68 saveRDS(dada.rev[[id]], file=paste("dada_", id,"_R2.Rdata", sep=""))
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69 }
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70
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71 # merge pairs
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72 print("mergePairs")
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73 merged <- mergePairs(dada.fwd, filt.fwd, dada.rev, filt.rev)
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74 for( id in sample.names ){
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75 saveRDS(merged[[id]], file=paste("mergePairs_", id,".Rdata", sep=""))
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76 }
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77
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78
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79 # make sequence table
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80 print("makeSequenceTable")
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81 seqtab <- makeSequenceTable(merged)
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82 write.table(t(seqtab), file="makeSequenceTable.tab", quote=F, sep="\t", row.names = T, col.names = NA)
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83
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84 reads.per.seqlen <- tapply(colSums(seqtab), factor(nchar(getSequences(seqtab))), sum)
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85 df <- data.frame(length=as.numeric(names(reads.per.seqlen)), count=reads.per.seqlen)
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86 pdf( 'makeSequenceTable.pdf' )
0
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87 ggplot(data=df, aes(x=length, y=count)) +
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88 geom_col() +
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89 theme_bw()
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90 bequiet <- dev.off()
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91
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92 # remove bimera
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93 print("removeBimera")
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94 seqtab.nochim <- removeBimeraDenovo(seqtab)
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95 write.table(t(seqtab), file="removeBimeraDenovo.tab", quote=F, sep="\t", row.names = T, col.names = NA)
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96
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97 # assign taxonomy/species
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98 tl <- 'Level1,Level2,Level3,Level4,Level5'
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99 tl <- strsplit(tl, ",")[[1]]
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100
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101 set.seed(42)
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102 print("assignTaxonomyAndSpecies")
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103 taxa <- assignTaxonomy(seqtab.nochim, 'reference.fa.gz', outputBootstraps = T, taxLevels=tl, multithread = 1)
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104
2
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105 taxa$tax <- addSpecies(taxa$tax, 'reference_species.fa.gz')
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106 write.table(taxa$tax, file = 'assignTaxonomyAddspecies.tab', quote = F, sep = "\t", row.names = T, col.names = NA)
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107
2
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108 write.table(taxa$boot, file = 'assignTaxonomyAddspecies_boot.tab', quote = F, sep = "\t", row.names = T, col.names = NA)
0
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109
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110
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111 ## Generate extra test data for parameter testing
2
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112 print("alternatives")
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113 filterAndTrim(fwd, c('filterAndTrim_single_F3D0_R1.fq.gz', 'filterAndTrim_single_F3D141_R1.fq.gz'), rm.phix = T, orient.fwd = 'TACGG')
0
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114
2
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115 filterAndTrim(fwd, c('filterAndTrim_single_trimmers_F3D0_R1.fq.gz', 'filterAndTrim_single_trimmers_F3D141_R1.fq.gz'), truncQ = 30, truncLen = 2, trimLeft = 150, trimRight = 2)
0
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116
2
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117 filterAndTrim(fwd, c('filterAndTrim_single_filters_F3D0_R1.fq.gz', 'filterAndTrim_single_filters_F3D141_R1.fq.gz'), maxLen = 255, minLen = 60, maxN = 100, minQ = 13, maxEE = 1)
0
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118
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119
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120 merged_nondef <- mergePairs(dada.fwd, filt.fwd, dada.rev, filt.rev, minOverlap = 8, maxMismatch = 1, justConcatenate = TRUE, trimOverhang = TRUE)
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121 for( id in sample.names ){
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122 saveRDS(merged_nondef[[id]], file=paste("mergePairs_", id,"_nondefault.Rdata", sep=""))
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123 }
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124 rb.dada.fwd <- removeBimeraDenovo(dada.fwd[["F3D0_S188_L001"]])
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125 write.table(rb.dada.fwd, file = 'removeBimeraDenovo_F3D0_dada_uniques.tab', quote = F, sep = "\t", row.names = T, col.names = F)
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126
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127 rb.merged <- removeBimeraDenovo(merged, method="pooled")
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128 saveRDS(rb.merged, file='removeBimeraDenovo_F3D0_mergepairs.Rdata')
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129
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130 # SeqCounts
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131 getN <- function(x){ sum(getUniques(x)) }
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132
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133 read.uniques <- function ( fname ) {
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134 p <- read.table(fname, header=F, sep="\t")
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135 n <-x[,2]
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136 names(n)<-x[,1]
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137 }
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138
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139
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140 print("seqCounts ft")
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141 samples = list()
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142 samples[["F3D0_S188_L001_R1_001.tab"]] <- read.table("F3D0_S188_L001_R1_001.tab", header=T, sep="\t", row.names=1)
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143 dname <- "filter"
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144 tdf <- samples[["F3D0_S188_L001_R1_001.tab"]]
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145 names(tdf) <- paste( dname, names(tdf) )
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146 tdf <- cbind( data.frame(samples=names( samples )), tdf)
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147 write.table(tdf, "seqCounts_filter.tab", quote=F, sep="\t", row.names = F, col.names = T)
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148
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149 samples = list()
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150 samples[["F3D0_S188_L001_R1_001.tab"]] <- read.table("F3D0_S188_L001_R1_001.tab", header=T, sep="\t", row.names=1)
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151 samples[["F3D141_S207_L001_R1_001.tab"]] <- read.table("F3D141_S207_L001_R1_001.tab", header=T, sep="\t", row.names=1)
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152 dname <- "filter"
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153 tdf <- samples[["F3D0_S188_L001_R1_001.tab"]]
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154 tdf <- rbind(tdf, samples[["F3D141_S207_L001_R1_001.tab"]])
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155 names(tdf) <- paste( dname, names(tdf) )
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156 tdf <- cbind( data.frame(samples=names( samples )), tdf)
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157 write.table(tdf, "seqCounts_filter_both.tab", quote=F, sep="\t", row.names = F, col.names = T)
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158
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159 print("seqCounts dada")
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160 samples = list()
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161 samples[["dada_F3D0_S188_L001_R1.Rdata"]] <- readRDS('dada_F3D0_S188_L001_R1.Rdata')
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162 samples[["dada_F3D141_S207_L001_R1.Rdata"]] <- readRDS('dada_F3D141_S207_L001_R1.Rdata')
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163 dname <- "dadaF"
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164 tdf <- data.frame( samples = names(samples) )
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165 tdf[[ dname ]] <- sapply(samples, getN)
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166 write.table(tdf, "seqCounts_dadaF.tab", quote=F, sep="\t", row.names = F, col.names = T)
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167
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168 print("seqCounts mp")
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169 samples = list()
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170 samples[["mergePairs_F3D0_S188_L001.Rdata"]] <- readRDS('mergePairs_F3D0_S188_L001.Rdata')
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171 samples[["mergePairs_F3D141_S207_L001.Rdata"]] <- readRDS('mergePairs_F3D141_S207_L001.Rdata')
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172 dname <- "merge"
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173 tdf <- data.frame( samples = names(samples) )
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174 tdf[[ dname ]] <- sapply(samples, getN)
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175 write.table(tdf, "seqCounts_merge.tab", quote=F, sep="\t", row.names = F, col.names = T)
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176
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177 print("seqCounts st")
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178 samples = list()
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179 samples <- t(as.matrix( read.table("makeSequenceTable.tab", header=T, sep="\t", row.names=1) ))
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180 dname <- "seqtab"
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181 tdf <- data.frame( samples = row.names(samples) )
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182 tdf[[ dname ]] <- rowSums(samples)
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183 write.table(tdf, "seqCounts_seqtab.tab", quote=F, sep="\t", row.names = F, col.names = T)
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184
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185 print("seqCounts rb")
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186 samples = list()
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187 samples <- t(as.matrix( read.table("removeBimeraDenovo.tab", header=T, sep="\t", row.names=1) ))
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188 dname <- "nochim"
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189 tdf <- data.frame( samples = row.names(samples) )
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190 tdf[[ dname ]] <- rowSums(samples)
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191 write.table(tdf, "seqCounts_nochim.tab", quote=F, sep="\t", row.names = F, col.names = T)
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192