When I was reading this paper:
I realized that even though it was believed that "for a given gene, the GC-content effect was the same across samples and hence would cancel out when considering DE statistics such as count ratios.", but now, this belief is disputed and they say, biases due to GC content should be normalized before DE analysis.
Now, I have a table of raw read counts. I analyzed the data without controlling for the GC content. I know that such effect can be absorbed into sample specific sequencing depth if only a single sample is sequenced in each lane. My data comes from an experiment in which two samples have been sequenced in each lane. How can I normalize the data if all I have is the table of raw read counts? Is it ok if I don't adjust the effect of GC content and normalize my data only for sequencing depth bias?