Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes.

Background: RNA-seq has become a standard technology to quantify mRNA. The measured values usually vary by several orders of magnitude, and while the detection of differences at high values is statistically well grounded, the significance of the differences for rare mRNAs can be weakened by the presence of biological and technical noise.

Results: We have developed a method for cleaning RNA-seq data, which improves the detection of differentially expressed genes and specifically genes with low to moderate transcription.