SNPlice: variants that modulate Intron retention from RNA-sequencing data.

ABSTRACT:

Rationale

The growing recognition of the importance of splicing, together with rapidly accumulating RNA-sequencing data, demand robust high-throughput approaches, which efficiently analyze experimentally derived whole-transcriptome splice profiles.

Results

We have developed a computational approach, called SNPlice, for identifying cis-acting, splice-modulating variants from RNA-seq datasets. SNPlice mines RNA-seq datasets to find reads that span single-nucleotide variant (SNV) loci and nearby splice junctions, assessing the co-occurrence of variants and molecules that remain unspliced at nearby exon-intron boundaries. Hence, SNPlice highlights variants preferentially occurring on intron-containing molecules, possibly resulting from altered splicing. To illustrate co-occurren

SUBMITTER: Mudvari P 

PROVIDER: S-EPMC4393518 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature