ArticleGenome biology2016
Modelling local gene networks increases power to detect trans-acting genetic effects on gene expression.
Article in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
14 citing papers in PubMed.
- Inferring cell-type-specific causal gene regulatory networks during human neurogenesis.Genome biology · 2023Article
- Telescoping bimodal latent Dirichlet allocation to identify expression QTLs across tissues.Life science alliance · 2022Article
- EPISPOT: An epigenome-driven approach for detecting and interpreting hotspots in molecular QTL studies.American journal of human genetics · 2021Article
- Tejaas: reverse regression increases power for detecting trans-eQTLs.Genome biology · 2021Article
- Efficient and effective control of confounding in eQTL mapping studies through joint differential expression and Mendelian randomization analyses.Bioinformatics (Oxford, England) · 2021Article
- LORSEN: Fast and Efficient eQTL Mapping With Low Rank Penalized Regression.Frontiers in genetics · 2021Article
- Article
- Tensor decomposition of stimulated monocyte and macrophage gene expression profiles identifies neurodegenerative disease-specific trans-eQTLs.PLoS genetics · 2020Article
- Identification of trans-eQTLs using mediation analysis with multiple mediators.BMC bioinformatics · 2019Article
- Interferon-stimulated genes: new platforms and computational approaches.Mammalian genome : official journal of the International Mammalian Genome Society · 2018Review
- Article
- Role of DNA Methylation in Type 2 Diabetes Etiology: Using Genotype as a Causal Anchor.Diabetes · 2017Article
- Joint genetic analysis using variant sets reveals polygenic gene-context interactions.PLoS genetics · 2017Article
- Deep learning for computational biology.Molecular systems biology · 2016Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Expression quantitative trait loci (eQTL) mapping is a widely used tool to study the genetics of gene expression. Confounding factors and the burden of multiple testing limit the ability to map distal trans eQTLs, which is important to understand downstream genetic effects on genes and pathways. We propose a two-stage linear mixed model that first learns local directed gene-regulatory networks to then condition on the expression levels of selected genes. We show that this covariate selection approach controls for confounding factors and regulatory context, thereby increasing eQTL detection power and improving the consistency between studies. GNet-LMM is available at: https://github.com/PMBio/GNetLMM.
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Registered trials
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.