PT  - JOURNAL ARTICLE
AU  - Emmanuel Dimont
AU  - Jiantao Shi
AU  - Rory Kirchner
AU  - Winston Hide
TI  - Gene Expression: edgeRun: an R package for sensitive, functionally relevant differential expression discovery using an unconditional exact test
AID  - 10.1101/008409
DP  - 2014 Jan 01
TA  - bioRxiv
PG  - 008409
4099  - http://biorxiv.org/content/early/2014/08/25/008409.short
4100  - http://biorxiv.org/content/early/2014/08/25/008409.full
AB  - Summary Next-generation sequencing platforms for measuring digital expression such as RNA-Seq are displacing traditional microarray-based methods in biological experiments. The detection of differentially expressed genes between groups of biological conditions has led to the development of numerous bioinformatics tools, but so far few, exploit the expanded dynamic range afforded by the new technologies. We present edgeRun, an R package that implements an unconditional exact test that is a more powerful version of the exact test in edgeR. This increase in power is especially pronounced for experiments with as few as 2 replicates per condition, for genes with low total expression and with large biological coefficient of variation. In comparison with a panel of other tools, edgeRun consistently captures functionally similar differentially expressed genes.Availability The package is freely available under the MIT license from CRAN (http://cran.r-project.org/web/packages/edgeRun)Contact edimont{at}mail.harvard.edu