ArticleNature communications2018
Genome-wide identification of directed gene networks using large-scale population genomics data.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 31 citations in OpenAlex.
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- Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networks.Genome research · 2025Article
- Mendelian randomization evidence for lung function mediates the association between childhood allergies (age <16 years) and essential hypertension.Reproductive and developmental medicine · 2025Article
- eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis.Cell genomics · 2024Article
- Genetically predicted dietary macronutrient intakes and atrial fibrillation risk: a Mendelian randomization study.European journal of medical research · 2024Article
- Trans-eQTL mapping in gene sets identifies network effects of genetic variants.Cell genomics · 2024Article
- Diabetes mellitus and prostate cancer risk: A mendelian randomization analysis.World journal of diabetes · 2023Article
- Network reconstruction for trans acting genetic loci using multi-omics data and prior information.Genome medicine · 2022Article
- Network-guided search for genetic heterogeneity between gene pairs.Bioinformatics (Oxford, England) · 2021Article
- Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids.Nature communications · 2020Article
- Article
- Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference.Genome biology · 2020Article
- GBAT: a gene-based association test for robust detection of trans-gene regulation.Genome biology · 2020Article
- Using regulatory variants to detect gene-gene interactions identifies networks of genes linked to cell immortalisation.Nature communications · 2020Article
- An omnidirectional visualization model of personalized gene regulatory networks.NPJ systems biology and applications · 2019Article
- Making Genetic Testing More Clinically Valuable.Integrative medicine (Encinitas, Calif.) · 2018Article
- Statistical and Machine Learning Approaches to Predict Gene Regulatory Networks From Transcriptome Datasets.Frontiers in plant science · 2018Review
Corrections and comments
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Authors and funding
20 authors at 7 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identification of causal drivers behind regulatory gene networks is crucial in understanding gene function. Here, we develop a method for the large-scale inference of gene-gene interactions in observational population genomics data that are both directed (using local genetic instruments as causal anchors, akin to Mendelian Randomization) and specific (by controlling for linkage disequilibrium and pleiotropy). Analysis of genotype and whole-blood RNA-sequencing data from 3072 individuals identified 49 genes as drivers of downstream transcriptional changes (Wald P < 7 × 10
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