Nov 22, 2018

ASGAL: aligning RNA-Seq data to a splicing graph to detect novel alternative splicing events

BMC Bioinformatics
Luca DentiPaola Bonizzoni

Abstract

While the reconstruction of transcripts from a sample of RNA-Seq data is a computationally expensive and complicated task, the detection of splicing events from RNA-Seq data and a gene annotation is computationally feasible. This latter task, which is adequate for many transcriptome analyses, is usually achieved by aligning the reads to a reference genome, followed by comparing the alignments with a gene annotation, often implicitly represented by a graph: the splicing graph. We present ASGAL (Alternative Splicing Graph ALigner): a tool for mapping RNA-Seq data to the splicing graph, with the specific goal of detecting novel splicing events, involving either annotated or unannotated splice sites. ASGAL takes as input the annotated transcripts of a gene and a RNA-Seq sample, and computes (1) the spliced alignments of each read in input, and (2) a list of novel events with respect to the gene annotation. An experimental analysis shows that ASGAL allows to enrich the annotation with novel alternative splicing events even when genes in an experiment express at most one isoform. Compared with other tools which use the spliced alignment of reads against a reference genome for differential analysis, ASGAL better predicts events that u...Continue Reading

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Mentioned in this Paper

Nested Transcripts
Genome
Genes
Sequence Determinations, RNA
Pythium sp. 4 eu
Nuclear mRNA Cis Splicing, via Spliceosome
Genes, vif
Device, Prosthesis Alignment
RNA Splicing
Gene Expression Profiling

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