title: 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.
authors.forename: Keyan
authors.initials: K
authors.lastname: Zhao
authors.forename: Zhi-xiang
authors.initials: ZX
authors.lastname: Lu
authors.forename: Juw Won
authors.initials: JW
authors.lastname: Park
authors.forename: Qing
authors.initials: Q
authors.lastname: Zhou
authors.forename: Yi
authors.initials: Y
authors.lastname: Xing
mesh_terms: D017398:Alternative Splicing / Q000235:genetics*; D034961:Antigens, Nuclear / Q000235:genetics; D003198:Computer Simulation; D030541:Databases, Genetic; D004194:Disease / Q000235:genetics; D055106:Genome-Wide Association Study; D006801:Humans; D015233:Models, Statistical; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D040641:Quantitative Trait Loci / Q000235:genetics; D019655:Quantitative Trait, Heritable; D017423:Sequence Analysis, RNA; D012984:Software; D014157:Transcription Factors / Q000235:genetics; D044465:White People / Q000235:genetics
chemical_list: D034961:Antigens, Nuclear; C102470:SP140 protein, human; D014157:Transcription Factors