derfinder-package: Annotation-agnostic differential expression analysis of RNA-seq data at base-pair resolution via the DER Finder approach.

Description

This package contains two different implementations of the DER Finder approach. The first one is the single base-level F-statistics implementation and the second one is via identifying expressed regions.

Arguments

Details

The single base-level F-statistics analysis pipeline involves loading the sample BAM files using rawFiles and loadCoverage, pre-processing the data by using preprocessCoverage, calculating the F-statistics (while adjusting for some confounders) using makeModels and calculateStats, calculating the p-values and finding the regions of interest using calculatePvalues, and finally annotating them using matchGenes from the bumphunter package.

The DER Finder at the expressed regions-level is done with the regionMatrix or railMatrix functions depending on the input data.

Details about both approaches are further described in the vignettes.

The DER Finder approach can also be used to identify differentially bounded ChIP-seq regions (peaks). In particular, analyzeChr has parameters that allow smoothing of the F-statistics which can be useful for anlayzing ChIP-seq data. This use case is further explained in the users guide vignette.

References

Collado-Torres L, Frazee AC, Love MI, Irizarry RA, Jaffe AE and Leek JT (2015). derfinder: Software for annotation-agnostic RNA-seq differential expression analysis. bioRxiv (2015). doi:10.1101/015370

Frazee, A. C., Sabunciyan, S., Hansen, K. D., Irizarry, R. A. & Leek, J. T. Differential expression analysis of RNA-seq data at single-base resolution. Biostatistics (2014). doi:10.1093/biostatistics/kxt053

Rafael A. Irizarry, Martin Aryee, Hector Corrada Bravo, Kasper D. Hansen and Harris A. Jaffee. bumphunter: Bump Hunter. R package version 1.1.10.