ArticleBioinformatics (Oxford, England)2012
Matrix eQTL: ultra fast eQTL analysis via large matrix operations.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,123 papers, 2 of them syntheses that pooled it.
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Who cites it
1,123 citing papers in PubMed, 2 syntheses or guidelines pooled it.
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- Identification and characterization of non-canonical azole antifungal resistance pathways inmBio · 2026Article
- Genetic and molecular evidence linking CTSH to Alzheimer's disease pathophysiology.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Tissue-resident immune cells drive genetic risk in autoimmune and lung diseases.Nature immunology · 2026Article
- Characterization of the chromosome 7 locus associated with suicidal behavior.Molecular psychiatry · 2026Article
- Expression quantitative trait methylation across multiple cancer types with functional and therapeutic characterization using Onco-eQTM.NAR genomics and bioinformatics · 2026Article
- HIV immunological nonresponders show low SKAP1 concentration and DNA hypermethylation in the SKAP1 promotor region.AIDS (London, England) · 2026Article
- FHL3 Regulates Vascular Smooth Muscle Cell Phenotypic Switching Through the MRTFB-SRF Signaling Axis.Cells · 2026Article
- Associations of host gene expression in the brain, liver, muscle with fecal and cecal microbiota composition in pigs.Functional & integrative genomics · 2026Article
- DetectGxT: detecting gene-by-treatment interactions on molecular count phenotypes accounting for allelic additivity.bioRxiv : the preprint server for biology · 2026Article
- Genome-wide DNA methylation analysis revealed epigenetic mechanism underlying end-stage renal disease.Nature communications · 2026Article
1,063 more citing papers are in PubMed but not listed here.
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Authors and funding
1 author.
Funding
Abstract
motivationExpression quantitative trait loci (eQTL) analysis links variations in gene expression levels to genotypes. For modern datasets, eQTL analysis is a computationally intensive task as it involves testing for association of billions of transcript-SNP (single-nucleotide polymorphism) pair. The heavy computational burden makes eQTL analysis less popular and sometimes forces analysts to restrict their attention to just a small subset of transcript-SNP pairs. As more transcripts and SNPs get interrogated over a growing number of samples, the demand for faster tools for eQTL analysis grows stronger.
resultsWe have developed a new software for computationally efficient eQTL analysis called Matrix eQTL. In tests on large datasets, it was 2-3 orders of magnitude faster than existing popular tools for QTL/eQTL analysis, while finding the same eQTLs. The fast performance is achieved by special preprocessing and expressing the most computationally intensive part of the algorithm in terms of large matrix operations. Matrix eQTL supports additive linear and ANOVA models with covariates, including models with correlated and heteroskedastic errors. The issue of multiple testing is addressed by calculating false discovery rate; this can be done separately for cis- and trans-eQTLs.
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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.