Considering dependence among genes and markers for false discovery control in eQTL mapping | Zendy

Liang Chen | Zendy; Tiejun Tong | Zendy; Hongyu Zhao | Zendy

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Considering dependence among genes and markers for false discovery control in eQTL mapping

Author(s) -

Liang Chen,

Tiejun Tong,

Hongyu Zhao

Publication year - 2008

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/btn373

Subject(s) - false discovery rate , multiple comparisons problem , false positive paradox , expression quantitative trait loci , linkage disequilibrium , biology , variance (accounting) , computational biology , quantitative trait locus , linkage (software) , estimator , false positives and false negatives , statistical hypothesis testing , computer science , genetics , statistics , gene , mathematics , artificial intelligence , haplotype , business , accounting , single nucleotide polymorphism , genotype

Multiple comparison adjustment is a significant and challenging statistical issue in large-scale biological studies. In previous studies, dependence among genes is largely ignored. However, such dependence may be strong for some genomic-scale studies such as genetical genomics [also called expression quantitative trait loci (eQTL) mapping] in which thousands of genes are treated as quantitative traits and mapped to different genetical markers. Besides the dependence among markers, the dependence among the expression levels of genes can also have a significant impact on data analysis and interpretation.

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