We're looking at 700+ genes, about 20 of which are considered housekeeping while the rest are endogenous. Based on the other posts about using nanostring data here is how I've set up my model
dds <- DESeqDataSetFromMatrix(countData = counts, colData = sampledata, design = ~var1+var2+var3)
dds <-estimateSizeFactors(dds, controlGenes = controlgenes$Class.Name) dds <-estimateDispersions(dds, fitType = "local") dds <-nbinomLRT(dds, reduced = ~var1+var2)
and for QA, my MA plot is graphed like this
resp <- lfcShrink(dds, coef="conditionBvsA", type="apeglm") idx <- c("ABC", "DEF", "GHI", "JKL","MNO", "PQR", "STU", "VWX") xlim <- c(1,5e6) ylim <- c(-3,3)
plotMA(resp,ylim=ylim,xlim=xlim) with(resp[idx,], points(baseMean, log2FoldChange, cex=1, lwd=2, col="orange"))
and the housekeeping genes, rather than lying on the x-axis, look like this [https://ibb.co/wCcydFS
am I on the right track here? why do the housekeeping genes fall like this? Any help is much appreciated! Thanks!