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INRICH: interval-based enrichment analysis for genome-wide association studies
Author(s) -
Susan J. Lee,
Colm O’Dushlaine,
Brett Thomas,
Shaun Purcell
Publication year - 2012
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/bts191
Subject(s) - linkage disequilibrium , genome wide association study , permutation (music) , computer science , genetic association , computational biology , robustness (evolution) , single nucleotide polymorphism , false discovery rate , genome , statistical power , multiple comparisons problem , type i and type ii errors , data mining , biology , genetics , gene , statistics , mathematics , physics , genotype , acoustics
Here we present INRICH (INterval enRICHment analysis), a pathway-based genome-wide association analysis tool that tests for enriched association signals of predefined gene-sets across independent genomic intervals. INRICH has wide applicability, fast running time and, most importantly, robustness to potential genomic biases and confounding factors. Such factors, including varying gene size and single-nucleotide polymorphism density, linkage disequilibrium within and between genes and overlapping genes with similar annotations, are often not accounted for by existing gene-set enrichment methods. By using a genomic permutation procedure, we generate experiment-wide empirical significance values, corrected for the total number of sets tested, implicitly taking overlap of sets into account. By simulation we confirm a properly controlled type I error rate and reasonable power of INRICH under diverse parameter settings. As a proof of principle, we describe the application of INRICH on the NHGRI GWAS catalog.

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