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JEPEGMIX2: improved gene-level joint analysis of eQTLs in cosmopolitan cohorts

MOTIVATION: To increase detection power, researchers use gene level analysis methods to aggregate weak marker signals. Due to gene expression controlling biological processes, researchers proposed aggregating signals for expression Quantitative Trait Loci (eQTL). Most gene-level eQTL methods make st...

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Detalles Bibliográficos
Autores principales: Chatzinakos, Chris, Lee, Donghyung, Webb, Bradley T, Vladimirov, Vladimir I, Kendler, Kenneth S, Bacanu, Silviu-Alin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860197/
https://www.ncbi.nlm.nih.gov/pubmed/28968763
http://dx.doi.org/10.1093/bioinformatics/btx509
Descripción
Sumario:MOTIVATION: To increase detection power, researchers use gene level analysis methods to aggregate weak marker signals. Due to gene expression controlling biological processes, researchers proposed aggregating signals for expression Quantitative Trait Loci (eQTL). Most gene-level eQTL methods make statistical inferences based on (i) summary statistics from genome-wide association studies (GWAS) and (ii) linkage disequilibrium patterns from a relevant reference panel. While most such tools assume homogeneous cohorts, our Gene-level Joint Analysis of functional SNPs in Cosmopolitan Cohorts (JEPEGMIX) method accommodates cosmopolitan cohorts by using heterogeneous panels. However, JEPGMIX relies on brain eQTLs from older gene expression studies and does not adjust for background enrichment in GWAS signals. RESULTS: We propose JEPEGMIX2, an extension of JEPEGMIX. When compared to JPEGMIX, it uses (i) cis-eQTL SNPs from the latest expression studies and (ii) brains specific (sub)tissues and tissues other than brain. JEPEGMIX2 also (i) avoids accumulating averagely enriched polygenic information by adjusting for background enrichment and (ii) to avoid an increase in false positive rates for studies with numerous highly enriched (above the background) genes, it outputs gene q-values based on Holm adjustment of P-values. AVAILABILITY AND IMPLEMENTATION: https://github.com/Chatzinakos/JEPEGMIX2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.