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Updated Practical 3 Processing 16S rRNA amplicon data (markdown) authored by Ben Francis's avatar Ben Francis
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Practical-3-Processing-16S-rRNA-amplicon-data.md
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...@@ -118,7 +118,7 @@ For now though, we're just going to use a (relatively) simple plotting function ...@@ -118,7 +118,7 @@ For now though, we're just going to use a (relatively) simple plotting function
seqtab <- seqtab/rowSums(seqtab) seqtab <- seqtab/rowSums(seqtab)
seqtab <- seqtab[, sapply(seqtab, function(x) max(x)) >= min_abund] seqtab <- seqtab[, sapply(seqtab, function(x) max(x)) >= min_abund]
seqtab$sample <- rownames(seqtab) seqtab$sample <- rownames(seqtab)
seqtab.m <- melt(seqtab.copy) seqtab.m <- melt(seqtab)
seqtab.m <- seqtab.m[grep(taxon, seqtab.m$variable),] seqtab.m <- seqtab.m[grep(taxon, seqtab.m$variable),]
seqtab.m$variable <- gsub("NA", "uncultured", seqtab.m$variable) seqtab.m$variable <- gsub("NA", "uncultured", seqtab.m$variable)
seqtab.m$variable <- as.character(seqtab.m$variable) seqtab.m$variable <- as.character(seqtab.m$variable)
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