%0 Journal Article %T Error estimates for the analysis of differential expression from RNA-seq count data %A Conrad J. Burden %A Sumaira E. Qureshi %A Susan R. Wilson %J PeerJ %D 2015 %I %R 10.7717/peerj.576 %X Background. A number of algorithms exist for analysing RNA-sequencing data to infer profiles of differential gene expression. Problems inherent in building algorithms around statistical models of over dispersed count data are formidable and frequently lead to non-uniform p-value distributions for null-hypothesis data and to inaccurate estimates of false discovery rates (FDRs). This can lead to an inaccurate measure of significance and loss of power to detect differential expression. %K RNA-seq %K Differential expression analysis %K False discovery rates %U https://peerj.com/articles/576/