Differential expression analysis of RNA sequencing (RNA-seq) data typically relies on reconstructing transcripts or counting reads that overlap known gene structures. Previously, researchers at Johns Hopkins Bloomberg School of Public Health introduced an intermediate approach called differentially expressed region (DER) finder that seeks to identify contiguous regions of the genome showing differential expression signal at single base resolution that does not rely on existing annotation or potentially inaccurate transcript discovery. However, there were computational challenges involved with performing base-resolution analyses in large numbers of samples at genome scale.
Here the researchers describe a new version of the derfinder software that allows for:
(1) genome- scale analyses in a large number of samples,
(2) flexible statistical modeling, including multi-group and time course analyses, and
(3) a new, computationally efficient approach to re-analysis at base resolution called expressed-region analysis.
The researchers also introduce functionality for annotating and plotting base-resolution data to identify artifacts and confirm results. They apply this approach to public RNA-seq data from the developing human brain to illustrate the types of analyses and results possible using derfinder. Conclusions Single-base and expressed-region RNA-sequencing analysis provides compromise between full transcript reconstruction and gene-level analysis. derfinder is software designed to identify, visualize, and interpret differentially expressed regions.
Availability – The package is available from Bioconductor at www.bioconductor.org/packages/release/bioc/html/derfinder.html