Thanks in advance for the help! I am still new to edgeR and welcome for any suggestions!
I am trying to figure out which method is better off to analyze my data. I am interesting in translational change before vs. after stress in yeast(s. cerevisiae). I carried out polysome profiles before and after stress, then RNA-seq of collected fractions of whole polysome profiles (total 9 fractions per polysome profile). During RNA sample extraction, I spike-in equal amount of RNA (from S.pombe) for later normalization. I used the normalized counts (based on spike-in counts), summed up the reads of polysome fractions(poly) and reads of the whole polysome profile(total), and tried to use the ratio (poly/total) to access the translation change. I have 2 biological replicates and 2 conditions, before and after stress. I have used the ratio number in limma and got reasonable results. Meanwhile, I also get suggestions to use edgeR with summed poly-counts as input and total counts as offsets. But, when I run the edgeR, it crushed after a certain code. Here is my code for running edgeR:
> x = DGEList(counts = inp) # inp contains normalized reads of summed polysome fractions
> x$offest = off # off is the sum of total reads, have the same dimension as inp
> x = estimateCommonDisp(x)
>x = estimateGLMTrendedDisp(x, design)
The R is crushed on this step.
Any suggestions and thoughts with my codes? I am also wondering what people think about using limma vs. edgeR for this analysis.