Work

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

Year: 2013

Type: article

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.

Source: Genome biology

DOI: 10.1186/gb-2013-14-7-r74

Authors: Keyan Zhao, Zhi-xiang Lu, Juw Won Park, Qing Zhou, Yi Xing

Institutions: University of Iowa, University of California, Los Angeles

Language: English

Topic: RNA Research and Splicing

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $5,490

Funders: March of Dimes Foundation, National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute of General Medical Sciences