# HG changeset patch
# User iuc
# Date 1594726679 14400
# Node ID bfd62e881837b358cb8e87273342de48e39be7dd
# Parent 99c6929236fa91496663fa39709972913e1a973d
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/dada2 commit 8533fe71d1d50f09348da2dc34941724407a1ffe"
diff -r 99c6929236fa -r bfd62e881837 macros.xml
--- a/macros.xml Mon Mar 16 07:54:26 2020 -0400
+++ b/macros.xml Tue Jul 14 07:37:59 2020 -0400
@@ -7,7 +7,7 @@
- 1.14
+ 1.16
0
@@ -124,6 +124,9 @@
.. image:: pairpipe.png
+Note: In particular for the analysis of paired collections the collections should be sorted lexicographical
+before the analysis.
+
For single end data you the steps "Unzip collection" and "mergePairs" are not necessary.
More information may be found on the dada2 homepage:: https://benjjneb.github.io/dada2/index.html (in particular tutorials) or the documentation of dada2's R package https://bioconductor.org/packages/release/bioc/html/dada2.html (in particular the pdf which contains the full documentation of all parameters)
diff -r 99c6929236fa -r bfd62e881837 static/images/pairpipe.png
Binary file static/images/pairpipe.png has changed
diff -r 99c6929236fa -r bfd62e881837 static/images/pairpipe.svg
--- a/static/images/pairpipe.svg Mon Mar 16 07:54:26 2020 -0400
+++ b/static/images/pairpipe.svg Tue Jul 14 07:37:59 2020 -0400
@@ -24,7 +24,7 @@
image/svg+xml
-
+
@@ -37,16 +37,16 @@
guidetolerance="10"
inkscape:pageopacity="0"
inkscape:pageshadow="2"
- inkscape:window-width="1920"
- inkscape:window-height="1016"
+ inkscape:window-width="1680"
+ inkscape:window-height="986"
id="namedview386"
showgrid="false"
inkscape:snap-global="true"
inkscape:snap-bbox="false"
inkscape:object-paths="true"
- inkscape:zoom="1"
- inkscape:cx="650.80177"
- inkscape:cy="176.12189"
+ inkscape:zoom="2"
+ inkscape:cx="336.68624"
+ inkscape:cy="192.12189"
inkscape:window-x="0"
inkscape:window-y="27"
inkscape:window-maximized="1"
@@ -443,22 +443,22 @@
plotQualityProfile
+ style="stroke:#000000;marker-end:url(#id2);stroke-width:0.93333333;stroke-miterlimit:4;stroke-dasharray:none" />
+ d="m 283.77925,110.5 h 33.78051"
+ style="stroke:#000000;stroke-width:0.93333333;marker-end:url(#id2);stroke-miterlimit:4;stroke-dasharray:none" />
@@ -524,7 +524,7 @@
sodipodi:role="line">and addSpecies
+ style="stroke:#000000;marker-end:url(#id2);stroke-width:0.93333333;stroke-miterlimit:4;stroke-dasharray:none" />
+ style="fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:0.93333333;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;marker-end:url(#id2);stroke-miterlimit:4;stroke-dasharray:none" />
+ style="stroke:#000000;marker-end:url(#id2);stroke-width:0.93333333;stroke-miterlimit:4;stroke-dasharray:none" />
+ style="stroke:#000000;marker-end:url(#id2);stroke-width:0.93333333;stroke-miterlimit:4;stroke-dasharray:none" />
+ transform="translate(-52.17332,-509.99998)">
filterAndTrim
- Unzip Collection
-
-
-
-
-
+ style="fill:none;fill-rule:evenodd;stroke:#000000;stroke-width:0.93333333;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;marker-end:url(#id2);stroke-miterlimit:4;stroke-dasharray:none" />
@@ -815,34 +779,34 @@
sodipodi:nodetypes="cc"
inkscape:connector-curvature="0"
id="path5609"
- d="M 117.55976,114.5 161.14262,20.499995"
- style="stroke:#000000;marker-end:url(#id2)" />
+ d="M 121.78486,109.34886 167.41518,39.34955"
+ style="stroke:#000000;stroke-width:0.93333334;stroke-miterlimit:4;stroke-dasharray:none;marker-end:url(#id2)" />
Paired input dataset collection
+ style="stroke:#000000;marker-end:url(#id2);stroke-width:0.93333333;stroke-miterlimit:4;stroke-dasharray:none" />
plotComplexity
+
+
+ Unzip & Sortdataset collection
+
+
+
diff -r 99c6929236fa -r bfd62e881837 test-data/gentest.R
--- a/test-data/gentest.R Mon Mar 16 07:54:26 2020 -0400
+++ b/test-data/gentest.R Tue Jul 14 07:37:59 2020 -0400
@@ -1,192 +1,186 @@
-library(dada2, quietly=T)
-library(ggplot2, quietly=T)
+library(dada2, quietly = T)
+library(ggplot2, quietly = T)
-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')
+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')
+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")
-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)
+for (i in seq_len(fwd)) {
+ ftout <- dada2::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,])
+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)
+write.table(t, "filterAndTrim.tab", quote = F, sep = "\t", col.names = NA)
-names(fwd) <- sample.names
-names(rev) <- sample.names
-names(filt.fwd) <- sample.names
-names(filt.rev) <- sample.names
+names(fwd) <- sample_names
+names(rev) <- sample_names
+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"))
+qp <- dada2::plotQualityProfile(fwd)
+ggsave("qualityProfile_fwd.pdf", qp, width = 20, height = 15, units = c("cm"))
+qp <- dada2::plotQualityProfile(rev)
+ggsave("qualityProfile_rev.pdf", qp, width = 20, height = 15, units = c("cm"))
+qp <- dada2::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"))
+cp <- dada2::plotComplexity(fwd)
+ggsave("complexity_fwd.pdf", cp, width = 20, height = 15, units = c("cm"))
+cp <- dada2::plotComplexity(rev)
+ggsave("complexity_rev.pdf", cp, width = 20, height = 15, units = c("cm"))
+cp <- dada2::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_R1.Rdata')
-plot <- plotErrors(err.fwd)
-ggsave('learnErrors_R1.pdf', plot, width = 20,height = 15,units = c("cm"))
+err_fwd <- dada2::learnErrors(filt_fwd)
+saveRDS(err_fwd, file = "learnErrors_R1.Rdata")
+plot <- dada2::plotErrors(err_fwd)
+ggsave("learnErrors_R1.pdf", plot, width = 20, height = 15, units = c("cm"))
-err.rev <- learnErrors(filt.rev)
-saveRDS(err.rev, file='learnErrors_R2.Rdata')
-plot <- plotErrors(err.rev)
-ggsave('learnErrors.pdf', plot, width = 20,height = 15,units = c("cm"))
+err_rev <- dada2::learnErrors(filt_rev)
+saveRDS(err_rev, file = "learnErrors_R2.Rdata")
+plot <- dada2::plotErrors(err_rev)
+ggsave("learnErrors.pdf", plot, width = 20, height = 15, units = c("cm"))
# dada
print("dada")
-dada.fwd <- dada(filt.fwd, err.fwd)
-dada.rev <- dada(filt.rev, err.rev)
-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=""))
+dada_fwd <- dada2::dada(filt_fwd, err_fwd)
+dada_rev <- dada2::dada(filt_rev, err_rev)
+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)
-for( id in sample.names ){
- saveRDS(merged[[id]], file=paste("mergePairs_", id,".Rdata", sep=""))
+merged <- dada2::mergePairs(dada_fwd, filt_fwd, dada_rev, filt_rev)
+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.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.pdf' )
-ggplot(data=df, aes(x=length, y=count)) +
+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.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.tab", quote=F, sep="\t", row.names = T, col.names = NA)
+seqtab_nochim <- dada2::removeBimeraDenovo(seqtab)
+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 <- "Level1,Level2,Level3,Level4,Level5"
tl <- strsplit(tl, ",")[[1]]
set.seed(42)
print("assignTaxonomyAndSpecies")
-taxa <- assignTaxonomy(seqtab.nochim, 'reference.fa.gz', outputBootstraps = T, taxLevels=tl, multithread = 1)
+taxa <- dada2::assignTaxonomy(seqtab_nochim, "reference.fa.gz", outputBootstraps = T, taxLevels = tl, multithread = 1)
-taxa$tax <- addSpecies(taxa$tax, 'reference_species.fa.gz')
-write.table(taxa$tax, file = 'assignTaxonomyAddspecies.tab', quote = F, sep = "\t", row.names = T, col.names = NA)
+taxa$tax <- dada2::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$boot, file = 'assignTaxonomyAddspecies_boot.tab', quote = F, sep = "\t", row.names = T, col.names = NA)
+write.table(taxa$boot, file = "assignTaxonomyAddspecies_boot.tab", quote = F, sep = "\t", row.names = T, col.names = NA)
-## Generate extra test data for parameter testing
+## Generate extra test data for parameter testing
print("alternatives")
-filterAndTrim(fwd, c('filterAndTrim_single_F3D0_R1.fq.gz', 'filterAndTrim_single_F3D141_R1.fq.gz'), rm.phix = T, orient.fwd = 'TACGG')
+dada2::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', 'filterAndTrim_single_trimmers_F3D141_R1.fq.gz'), truncQ = 30, truncLen = 2, trimLeft = 150, trimRight = 2)
+dada2::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', 'filterAndTrim_single_filters_F3D141_R1.fq.gz'), maxLen = 255, minLen = 60, maxN = 100, minQ = 13, maxEE = 1)
+dada2::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)
-for( id in sample.names ){
- saveRDS(merged_nondef[[id]], file=paste("mergePairs_", id,"_nondefault.Rdata", sep=""))
+merged_nondef <- dada2::mergePairs(dada_fwd, filt_fwd, dada_rev, filt_rev, minOverlap = 8, maxMismatch = 1, justConcatenate = TRUE, trimOverhang = TRUE)
+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_dada_fwd <- dada2::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')
-
+rb_merged <- dada2::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]
+get_n <- function(x) {
+ sum(dada2::getUniques(x))
}
-
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)
+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)
+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)
+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)
+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')
+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)
+tdf <- data.frame(samples = names(samples))
+tdf[[dname]] <- sapply(samples, get_n)
+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')
+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)
+tdf <- data.frame(samples = names(samples))
+tdf[[dname]] <- sapply(samples, get_n)
+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) ))
+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)
+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) ))
+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)
-
+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)
diff -r 99c6929236fa -r bfd62e881837 test-data/learnErrors.pdf
Binary file test-data/learnErrors.pdf has changed
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