HEFT: eQTL analysis of many thousands of expressed genes while simultaneously controlling for hidden factors | Zendy

Chuan Gao | Zendy; Nicole Tignor | Zendy; Jacqueline Salit | Zendy; Yael StruloviciBarel | Zendy; Neil R. Hackett | Zendy; Ronald G. Crystal | Zendy; Jason G. Mezey | Zendy

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HEFT: eQTL analysis of many thousands of expressed genes while simultaneously controlling for hidden factors

Author(s) -

Chuan Gao,

Nicole Tignor,

Jacqueline Salit,

Yael StruloviciBarel,

Neil R. Hackett,

Ronald G. Crystal,

Jason G. Mezey

Publication year - 2013

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btt690

Subject(s) - expression quantitative trait loci , univariate , computational biology , biology , single nucleotide polymorphism , computer science , artificial intelligence , genetics , gene , machine learning , multivariate statistics , genotype

Identification of expression Quantitative Trait Loci (eQTL), the genetic loci that contribute to heritable variation in gene expression, can be obstructed by factors that produce variation in expression profiles if these factors are unmeasured or hidden from direct analysis.

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