Intron-centric estimation of alternative splicing from RNA-seq data

  • Dmitri D. Pervouchine
    1 Centre de Regulació Genòmica (CRG) and 2Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain and 3Moscow State University, 119992 Moscow, Russia
  • David G. Knowles
    1 Centre de Regulació Genòmica (CRG) and 2Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain and 3Moscow State University, 119992 Moscow, Russia
  • Roderic Guigó
    1 Centre de Regulació Genòmica (CRG) and 2Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain and 3Moscow State University, 119992 Moscow, Russia

Abstract

<jats:title>Abstract</jats:title> <jats:p>Motivation: Novel technologies brought in unprecedented amounts of high-throughput sequencing data along with great challenges in their analysis and interpretation. The percent-spliced-in (PSI, ) metric estimates the incidence of single-exon–skipping events and can be computed directly by counting reads that align to known or predicted splice junctions. However, the majority of human splicing events are more complex than single-exon skipping.</jats:p> <jats:p>Results: In this short report, we present a framework that generalizes the metric to arbitrary classes of splicing events. We change the view from exon centric to intron centric and split the value of into two indices, and , measuring the rate of splicing at the 5′ and 3′ end of the intron, respectively. The advantage of having two separate indices is that they deconvolute two distinct elementary acts of the splicing reaction. The completeness of splicing index is decomposed in a similar way. This framework is implemented as bam2ssj, a BAM-file–processing pipeline for strand-specific counting of reads that align to splice junctions or overlap with splice sites. It can be used as a consistent protocol for quantifying splice junctions from RNA-seq data because no such standard procedure currently exists.</jats:p> <jats:p>Availability: The C code of bam2ssj is open source and is available at https://github.com/pervouchine/bam2ssj</jats:p> <jats:p>Contact:  dp@crg.eu</jats:p>

Journal

  • Bioinformatics

    Bioinformatics 29 (2), 273-274, 2012-11-21

    Oxford University Press (OUP)

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