In section 5.2 of the diffHic manual (Removing trended biases between libraries), why is the MA plot plotted for two non-replicate samples in the input data?
input <- c("merged_flox_1.h5", "merged_flox_2.h5", "merged_ko_1.h5", "merged_ko_2.h5") data <- squareCounts(input, width=1e6, param=param)
<...>
ab <- aveLogCPM(asDGEList(data)) o <- order(ab) adj.counts <- cpm(asDGEList(data), log=TRUE) mval <- adj.counts[,3]-adj.counts[,2] smoothScatter(ab, mval, xlab="A", ylab="M", main="KO vs. Flox") fit <- loessFit(x=ab, y=mval) lines(ab[o], fit$fitted[o], col="red")
When I run this code, adj.counts is a matrix of the format:
Sample1 Sample2 Sample3 Sample4
1 1.8188661 2.3363146 1.7343820 1.6612176 2 2.5522622 3.7050666 2.8758002 2.7878327 3 4.5796852 5.3595436 4.7326327 4.4682953
I'm confused: why are we exploring the single trended dispersion for "merged_ko_1.h5" - "merged_flox_2.h5"?
Why aren't we exploring two plots for "merged_ko_1.h5" - "merged_flox_1.h5" *AND* "merged_ko_2.h5" - "merged_flox_2.h5"???
Thanks! I was just confused why the trended M-value was being compared between two non-replicate samples.