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Genome Biol. 2013 Jul 22;14(7):R74. doi: 10.1186/gb-2013-14-7-r74.

GLiMMPS: robust statistical model for regulatory variation of alternative splicing using RNA-seq data.

Abstract

To characterize the genetic variation of alternative splicing, we develop GLiMMPS, a robust statistical method for detecting splicing quantitative trait loci (sQTLs) from RNA-seq data. GLiMMPS takes into account the individual variation in sequencing coverage and the noise prevalent in RNA-seq data. Analyses of simulated and real RNA-seq datasets demonstrate that GLiMMPS outperforms competing statistical models. Quantitative RT-PCR tests of 26 randomly selected GLiMMPS sQTLs yielded a validation rate of 100%. As population-scale RNA-seq studies become increasingly affordable and popular, GLiMMPS provides a useful tool for elucidating the genetic variation of alternative splicing in humans and model organisms.

PMID:
23876401
[PubMed - in process]
PMCID:
PMC4054007
Free PMC Article

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