Mercurial > repos > iuc > dada2_assigntaxonomyaddspecies
diff test-data/gentest.R @ 2:1c9715cef808 draft
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit f2a33fe115fef9d711112b53136cf7619f1b19be"
author | iuc |
---|---|
date | Mon, 16 Mar 2020 08:03:24 -0400 |
parents | 18517edb4733 |
children | 79212a309499 |
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--- a/test-data/gentest.R Thu Dec 05 18:00:57 2019 -0500 +++ b/test-data/gentest.R Mon Mar 16 08:03:24 2020 -0400 @@ -1,99 +1,192 @@ library(dada2, quietly=T) library(ggplot2, quietly=T) -fwd <- c('F3D0_S188_L001_R1_001.fastq.gz') -rev <- c('F3D0_S188_L001_R2_001.fastq.gz') +sample.names <- c('F3D0_S188_L001', 'F3D141_S207_L001') +fwd <- c('F3D0_S188_L001_R1_001.fastq.gz', 'F3D141_S207_L001_R1_001.fastq.gz') +rev <- c('F3D0_S188_L001_R2_001.fastq.gz', 'F3D141_S207_L001_R2_001.fastq.gz') + +filt.fwd <- c('filterAndTrim_F3D0_R1.fq.gz', 'filterAndTrim_F3D141_R1.fq.gz') +filt.rev <- c('filterAndTrim_F3D0_R2.fq.gz', 'filterAndTrim_F3D141_R2.fq.gz') + +print("filterAndTrim") -sample.names <- c('F3D0_S188_L001') +for(i in 1:length(fwd)){ + ftout <- filterAndTrim(fwd[i], filt.fwd[i], rev[i], filt.rev[i]) + b <- paste(strsplit(fwd[i], ".", fixed=T)[[1]][1], "tab", sep=".") + write.table(ftout, b, quote=F, sep="\t", col.names=NA) +} + +# In the test only the 1st data set is used +t <- data.frame() +t <- rbind(t, ftout[1,]) +colnames(t) <- colnames(ftout) +rownames(t) <- rownames(ftout)[1] +write.table(t, "filterAndTrim.tab", quote=F, sep="\t", col.names=NA) names(fwd) <- sample.names names(rev) <- sample.names - - -filt.fwd <- c('filterAndTrim_F3D0_R1.fq.gz') -filt.rev <- c('filterAndTrim_F3D0_R2.fq.gz') - -ftout <- filterAndTrim(fwd, filt.fwd, rev, filt.rev) - -# In the test no name can be given to the collection -rownames(ftout) <- c( 'Unnamed Collection' ) -write.table(ftout, "filterAndTrim_F3D0.tab", quote=F, sep="\t", col.names=NA) +names(filt.fwd) <- sample.names +names(filt.rev) <- sample.names # Plot quality profile (just for one file, Galaxy compares with sim_size) - +print("plots") qp <- plotQualityProfile(fwd) +ggsave('qualityProfile_fwd.pdf', qp, width = 20,height = 15,units = c("cm")) +qp <- plotQualityProfile(rev) +ggsave('qualityProfile_rev.pdf', qp, width = 20,height = 15,units = c("cm")) +qp <- plotQualityProfile(fwd[1]) ggsave('qualityProfile.pdf', qp, width = 20,height = 15,units = c("cm")) # Plot complexity (just for one file, Galaxy compares with sim_size) cp <- plotComplexity(fwd) +ggsave('complexity_fwd.pdf', cp, width = 20,height = 15,units = c("cm")) +cp <- plotComplexity(rev) +ggsave('complexity_rev.pdf', cp, width = 20,height = 15,units = c("cm")) +cp <- plotComplexity(fwd[1]) ggsave('complexity.pdf', cp, width = 20,height = 15,units = c("cm")) # learn Errors +print("learnErrors") err.fwd <- learnErrors(filt.fwd) -saveRDS(err.fwd, file='learnErrors_F3D0_R1.Rdata') +saveRDS(err.fwd, file='learnErrors_R1.Rdata') plot <- plotErrors(err.fwd) -ggsave('learnErrors_F3D0_R1.pdf', plot, width = 20,height = 15,units = c("cm")) +ggsave('learnErrors_R1.pdf', plot, width = 20,height = 15,units = c("cm")) -err.rev <- learnErrors(filt.fwd) -saveRDS(err.rev, file='learnErrors_F3D0_R2.Rdata') +err.rev <- learnErrors(filt.rev) +saveRDS(err.rev, file='learnErrors_R2.Rdata') plot <- plotErrors(err.rev) -ggsave('learnErrors_F3D0_R2.pdf', plot, width = 20,height = 15,units = c("cm")) +ggsave('learnErrors.pdf', plot, width = 20,height = 15,units = c("cm")) -# dada +# dada +print("dada") dada.fwd <- dada(filt.fwd, err.fwd) -saveRDS(dada.fwd, file="dada_F3D0_R1.Rdata") dada.rev <- dada(filt.rev, err.rev) -saveRDS(dada.rev, file="dada_F3D0_R2.Rdata") +for( id in sample.names ){ + saveRDS(dada.fwd[[id]], file=paste("dada_", id,"_R1.Rdata", sep="")) + saveRDS(dada.rev[[id]], file=paste("dada_", id,"_R2.Rdata", sep="")) +} # merge pairs +print("mergePairs") merged <- mergePairs(dada.fwd, filt.fwd, dada.rev, filt.rev) -saveRDS(merged, file='mergePairs_F3D0.Rdata') +for( id in sample.names ){ + saveRDS(merged[[id]], file=paste("mergePairs_", id,".Rdata", sep="")) +} + # make sequence table +print("makeSequenceTable") seqtab <- makeSequenceTable(merged) -write.table(t(seqtab), file="makeSequenceTable_F3D0.tab", quote=F, sep="\t", row.names = T, col.names = NA) +write.table(t(seqtab), file="makeSequenceTable.tab", quote=F, sep="\t", row.names = T, col.names = NA) reads.per.seqlen <- tapply(colSums(seqtab), factor(nchar(getSequences(seqtab))), sum) df <- data.frame(length=as.numeric(names(reads.per.seqlen)), count=reads.per.seqlen) -pdf( 'makeSequenceTable_F3D0.pdf' ) +pdf( 'makeSequenceTable.pdf' ) ggplot(data=df, aes(x=length, y=count)) + geom_col() + theme_bw() bequiet <- dev.off() # remove bimera +print("removeBimera") seqtab.nochim <- removeBimeraDenovo(seqtab) -write.table(t(seqtab), file="removeBimeraDenovo_F3D0.tab", quote=F, sep="\t", row.names = T, col.names = NA) +write.table(t(seqtab), file="removeBimeraDenovo.tab", quote=F, sep="\t", row.names = T, col.names = NA) # assign taxonomy/species tl <- 'Level1,Level2,Level3,Level4,Level5' tl <- strsplit(tl, ",")[[1]] -taxa <- assignTaxonomy(seqtab.nochim, 'reference.fa', outputBootstraps = T, taxLevels=c('Level1','Level2','Level3','Level4','Level5')) +set.seed(42) +print("assignTaxonomyAndSpecies") +taxa <- assignTaxonomy(seqtab.nochim, 'reference.fa.gz', outputBootstraps = T, taxLevels=tl, multithread = 1) -taxa$tax <- addSpecies(taxa$tax, 'reference_species.fa') -write.table(taxa$tax, file = 'assignTaxonomyAddspecies_F3D0.tab', quote = F, sep = "\t", row.names = T, col.names = NA) +taxa$tax <- addSpecies(taxa$tax, 'reference_species.fa.gz') +write.table(taxa$tax, file = 'assignTaxonomyAddspecies.tab', quote = F, sep = "\t", row.names = T, col.names = NA) -write.table(taxa$boot, file = 'assignTaxonomyAddspecies_F3D0_boot.tab', quote = F, sep = "\t", row.names = T, col.names = NA) - +write.table(taxa$boot, file = 'assignTaxonomyAddspecies_boot.tab', quote = F, sep = "\t", row.names = T, col.names = NA) ## Generate extra test data for parameter testing - -filterAndTrim(fwd, c('filterAndTrim_single_F3D0_R1.fq.gz'), rm.phix = T, orient.fwd = 'TACGG') +print("alternatives") +filterAndTrim(fwd, c('filterAndTrim_single_F3D0_R1.fq.gz', 'filterAndTrim_single_F3D141_R1.fq.gz'), rm.phix = T, orient.fwd = 'TACGG') -filterAndTrim(fwd, c('filterAndTrim_single_trimmers_F3D0_R1.fq.gz'), truncQ = 30, truncLen = 2, trimLeft = 150, trimRight = 2) +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) -filterAndTrim(fwd, c('filterAndTrim_single_filters_F3D0_R1.fq.gz'), maxLen = 255, minLen = 60, maxN = 100, minQ = 13, maxEE = 1) +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) merged_nondef <- mergePairs(dada.fwd, filt.fwd, dada.rev, filt.rev, minOverlap = 8, maxMismatch = 1, justConcatenate = TRUE, trimOverhang = TRUE) -saveRDS(merged_nondef, file='mergePairs_F3D0_nondefault.Rdata') - -rb.dada.fwd <- removeBimeraDenovo(dada.fwd) +for( id in sample.names ){ + saveRDS(merged_nondef[[id]], file=paste("mergePairs_", id,"_nondefault.Rdata", sep="")) +} +rb.dada.fwd <- removeBimeraDenovo(dada.fwd[["F3D0_S188_L001"]]) write.table(rb.dada.fwd, file = 'removeBimeraDenovo_F3D0_dada_uniques.tab', quote = F, sep = "\t", row.names = T, col.names = F) rb.merged <- removeBimeraDenovo(merged, method="pooled") saveRDS(rb.merged, file='removeBimeraDenovo_F3D0_mergepairs.Rdata') + +# SeqCounts +getN <- function(x){ sum(getUniques(x)) } + +read.uniques <- function ( fname ) { + p <- read.table(fname, header=F, sep="\t") + n <-x[,2] + names(n)<-x[,1] +} + + +print("seqCounts ft") +samples = list() +samples[["F3D0_S188_L001_R1_001.tab"]] <- read.table("F3D0_S188_L001_R1_001.tab", header=T, sep="\t", row.names=1) +dname <- "filter" +tdf <- samples[["F3D0_S188_L001_R1_001.tab"]] +names(tdf) <- paste( dname, names(tdf) ) +tdf <- cbind( data.frame(samples=names( samples )), tdf) +write.table(tdf, "seqCounts_filter.tab", quote=F, sep="\t", row.names = F, col.names = T) + +samples = list() +samples[["F3D0_S188_L001_R1_001.tab"]] <- read.table("F3D0_S188_L001_R1_001.tab", header=T, sep="\t", row.names=1) +samples[["F3D141_S207_L001_R1_001.tab"]] <- read.table("F3D141_S207_L001_R1_001.tab", header=T, sep="\t", row.names=1) +dname <- "filter" +tdf <- samples[["F3D0_S188_L001_R1_001.tab"]] +tdf <- rbind(tdf, samples[["F3D141_S207_L001_R1_001.tab"]]) +names(tdf) <- paste( dname, names(tdf) ) +tdf <- cbind( data.frame(samples=names( samples )), tdf) +write.table(tdf, "seqCounts_filter_both.tab", quote=F, sep="\t", row.names = F, col.names = T) + +print("seqCounts dada") +samples = list() +samples[["dada_F3D0_S188_L001_R1.Rdata"]] <- readRDS('dada_F3D0_S188_L001_R1.Rdata') +samples[["dada_F3D141_S207_L001_R1.Rdata"]] <- readRDS('dada_F3D141_S207_L001_R1.Rdata') +dname <- "dadaF" +tdf <- data.frame( samples = names(samples) ) +tdf[[ dname ]] <- sapply(samples, getN) +write.table(tdf, "seqCounts_dadaF.tab", quote=F, sep="\t", row.names = F, col.names = T) + +print("seqCounts mp") +samples = list() +samples[["mergePairs_F3D0_S188_L001.Rdata"]] <- readRDS('mergePairs_F3D0_S188_L001.Rdata') +samples[["mergePairs_F3D141_S207_L001.Rdata"]] <- readRDS('mergePairs_F3D141_S207_L001.Rdata') +dname <- "merge" +tdf <- data.frame( samples = names(samples) ) +tdf[[ dname ]] <- sapply(samples, getN) +write.table(tdf, "seqCounts_merge.tab", quote=F, sep="\t", row.names = F, col.names = T) + +print("seqCounts st") +samples = list() +samples <- t(as.matrix( read.table("makeSequenceTable.tab", header=T, sep="\t", row.names=1) )) +dname <- "seqtab" +tdf <- data.frame( samples = row.names(samples) ) +tdf[[ dname ]] <- rowSums(samples) +write.table(tdf, "seqCounts_seqtab.tab", quote=F, sep="\t", row.names = F, col.names = T) + +print("seqCounts rb") +samples = list() +samples <- t(as.matrix( read.table("removeBimeraDenovo.tab", header=T, sep="\t", row.names=1) )) +dname <- "nochim" +tdf <- data.frame( samples = row.names(samples) ) +tdf[[ dname ]] <- rowSums(samples) +write.table(tdf, "seqCounts_nochim.tab", quote=F, sep="\t", row.names = F, col.names = T) +