Practical-3-Processing-16S-rRNA-amplicon-data.md

@@ -87,8 +87,7 @@ Now we need to make sure that we didn't lose too many sequences along the way, b
 Don't worry about what this code is actually doing (clearly the developer knew what they were doing to come up with this, but I don't). The point is that it gives you a table showing what happened at each step of the pipeline.
 
     > getN <- function(x) sum(getUniques(x))
-    > track <- cbind(out, sapply(dadaFs, getN), sapply(dadaRs, getN), sapply(mergers, getN), 
-          rowSums(seqtab.nochim))
+    > track <- cbind(out, sapply(dadaFs, getN), sapply(dadaRs, getN), sapply(mergers, getN), rowSums(seqtab.nochim))
     > colnames(track) <- c("input", "filtered", "denoisedF", "denoisedR", "merged", "nonchim")
     > rownames(track) <- sample.names
     > head(track)