Abstract
BackgroundAlternative splicing plays important roles in many regulatory processes and diseases in human. Many genetic variants contribute to phenotypic differences in gene expression and splicing that determine variations in human traits. Detecting genetic variants that affect splicing phenotypes is essential for understanding the functional impact of genetic variations on alternative splicing. For many situations, the key phenotype is the relative splicing ratios of alternative isoforms rather than the expression values of individual isoforms. Splicing quantitative trait loci (sQTL) analysis methods have been proposed for detecting associations of genetic variants with the vectors of isoform splicing ratios of genes. We call this task as composite sQTL analysis. Existing methods are computationally intensive and cannot scale up for whole genome analysis.ResultsWe developed an ultra-fast method named ulfasQTL for this task based on a previous method sQTLseekeR. It transforms tests of splicing ratios of multiple genes to a matrix form for efficient computation, and therefore can be applied for sQTL analysis at whole-genome scales at the speed thousands times faster than the existing method. We tested ulfasQTL on the data from the GEUVADIS project and compared it with an existing method.ConclusionsulfasQTL is a very efficient tool for composite splicing QTL analysis and can be applied on whole-genome analysis with acceptable time.
Highlights
Alternative splicing plays important roles in many regulatory processes and diseases in human
Expression quantitative trait loci analysis is an effective approach for studying the association between genetic variants and gene expression [11,12,13,14,15,16]
The patterns of the splicing ratios are very different among samples of different genotypes of the variant, which indicates that the variant is a splicing-QTL or Splicing quantitative trait loci (sQTL) of the gene
Summary
Alternative splicing plays important roles in many regulatory processes and diseases in human. Splicing quantitative trait loci (sQTL) analysis methods have been proposed for detecting associations of genetic variants with the vectors of isoform splicing ratios of genes. Expression quantitative trait loci (eQTL) analysis is an effective approach for studying the association between genetic variants and gene expression [11,12,13,14,15,16] This strategy has been extended to the analysis of association of alternative splicing genes with genetic variants [15, 17,18,19,20,21,22,23,24,25,26,27,28,29]. Exons in one gene are not independent and they compose multiple isoforms through
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