Introduction

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.

Publications

  1. GLiMMPS: robust statistical model for regulatory variation of alternative splicing using RNA-seq data.
    Cite this
    Zhao K, Lu ZX, Park JW, Zhou Q, Xing Y, 2013-07-01 - Genome biology

Credits

  1. Keyan Zhao
    Developer

  2. Zhi-xiang Lu
    Developer

  3. Juw Won Park
    Developer

  4. Qing Zhou
    Developer

  5. Yi Xing
    Investigator

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Summary
AccessionBT001803
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesPerl, R
User InterfaceTerminal Command Line
Download Count0
Submitted ByYi Xing