ArticleBioinformatics (Oxford, England)2013
iBMQ: a R/Bioconductor package for integrated Bayesian modeling of eQTL data.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- scQTLtools: An R/Bioconductor Package for Comprehensive Identification and Visualization of Single-Cell eQTLs.Biology · 2025Article
- Molecular mechanisms underpinning quantitative resistance toFrontiers in plant science · 2023Article
- RNA Biogenesis Instructs Functional Inter-Chromosomal Genome Architecture.Frontiers in genetics · 2021Article
- Development of a tissue augmented Bayesian model for expression quantitative trait loci analysis.Mathematical biosciences and engineering : MBE · 2019Article
- Statistical Methods in Integrative Genomics.Annual review of statistics and its application · 2016Article
- Bayesian Partition Models for Identifying Expression Quantitative Trait Loci.Journal of the American Statistical Association · 2015Article
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Authors and funding
5 authors.
Funding
Abstract
motivationRecently, mapping studies of expression quantitative loci (eQTL) (where gene expression levels are viewed as quantitative traits) have provided insight into the biology of gene regulation. Bayesian methods provide natural modeling frameworks for analyzing eQTL studies, where information shared across markers and/or genes can increase the power to detect eQTLs. Bayesian approaches tend to be computationally demanding and require specialized software. As a result, most eQTL studies use univariate methods treating each gene independently, leading to suboptimal results.
resultsWe present a powerful, computationally optimized and free open-source R package, iBMQ. Our package implements a joint hierarchical Bayesian model where all genes and SNPs are modeled concurrently. Model parameters are estimated using a Markov chain Monte Carlo algorithm. The free and widely used openMP parallel library speeds up computation. Using a mouse cardiac dataset, we show that iBMQ improves the detection of large trans-eQTL hotspots compared with other state-of-the-art packages for eQTL analysis. AVAILABILITY: The R-package iBMQ is available from the Bioconductor Web site at http://bioconductor.org and runs on Linux, Windows and MAC OS X. It is distributed under the Artistic Licence-2.0 terms. CONTACT: christian.deschepper@ircm.qc.ca or rgottard@fhcrc.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.