Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses.

ABSTRACT: Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance m

SUBMITTER: Liu R 

PROVIDER: S-EPMC4551905 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature