Most of DE tools (such as DE-Seq) applied in RNA-Seq assume that gene expression follows Negative Binomial distribution (because of both technical and biological variation). While DE tools originated from Microarray (such as limma) assumes normal distribution? Is this difference due to some technical difference between RNA-Seq and Microarray?
RNA-seq is count data (discrete), microarray is measured data (continuous). This is a pretty big difference to start with.
From what I understanding, counting reads from RNA-Seq is like sampling reads aligned on specific gene from reads pool. It represents Poisson process where we have small p (probability) and large n (total reads). Plus we have biological variation between samples. Therefore, we got Poisson with larger variance ~ Negative Binomial distribution. For Microarray data, I imagine we intuitively have the same technical variation (Poisson) and biological variation. Would not this form NB distribution as well instead of normal distribution?