**0**wrote:

Hi,

I am trying to understand and compare the DESeq2 model and the BNB-R (https://github.com/siamakz/BNBR) model. The corresponding references are:

- DESeq2: Love, M. I., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15(12), 550. https://doi.org/10.1186/s13059-014-0550-8
- BNB-R: Dadaneh, S. Z., Zhou, M., & Qian, X. (2018). Bayesian negative binomial regression for differential expression with confounding factors. Bioinformatics, 34(19), 3349–3356. https://doi.org/10.1093/bioinformatics/bty330

My understanding of the BNB-R model is that it regards the sample-specific size factor `r_j`

of the negative binomial distribution as a parameter that has to be estimated through Bayesian inference (i.e. sampling from its posterior). In DESeq2, there is a pre-estimated sample-specific size factor `s_j`

included in the mean, but there is also the dispersion parameter `alpha_i`

. Therefore, am I right that DESeq2 imposes additional overdispersion (having the pre-estimated size factors `s_j`

*as well as* `alpha_i`

)?