ArticleBioinformatics (Oxford, England)2011
dmGWAS: dense module searching for genome-wide association studies in protein-protein interaction networks.
Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 173 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
173 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Discovery of new risk loci for IgA nephropathy implicates genes involved in immunity against intestinal pathogens.Nature genetics · 2014Pooled it
- Network-based multiple sclerosis pathway analysis with GWAS data from 15,000 cases and 30,000 controls.American journal of human genetics · 2013Pooled it
- Network-assisted investigation of combined causal signals from genome-wide association studies in schizophrenia.PLoS computational biology · 2012Pooled it
- Analysis of gene-gene interactions among common variants in candidate cardiovascular genes in coronary artery disease.PloS one · 2015Trial
- In vivo mapping of protein-protein interactions of schizophrenia risk factors generates an interconnected disease network.Schizophrenia (Heidelberg, Germany) · 2026Article
- Identification and prioritization of gene sets associated with schizophrenia risk by network analysis.Psychopharmacology · 2026Article
- Identifying compounds to treat opiate use disorder by leveraging multi-omic data integration and multiple drug repurposing databases.Translational psychiatry · 2025Article
- CD40LG as a Biomarker in Rheumatoid Arthritis: Links to Bone Destruction and Interstitial Lung Disease - A Bioinformatic Analysis With Clinical Validation.Health science reports · 2025Article
- Genetic, Transcriptomic, and Epigenomic Insights into Sjögren's Disease: An Integrative Network Investigation and Immune Diseases Comparison.International journal of molecular sciences · 2025Article
- The goldmine of GWAS summary statistics: a systematic review of methods and tools.BioData mining · 2024Article
- Unveiling Gene Interactions in Alzheimer's Disease by Integrating Genetic and Epigenetic Data with a Network-Based Approach.Epigenomes · 2024Article
- Identifying key genes in COPD risk via multiple population data integration and gene prioritization.PloS one · 2024Article
- Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations.Nature communications · 2023Article
- Predicting disease genes based on multi-head attention fusion.BMC bioinformatics · 2023Article
- A gene regulatory network approach harmonizes genetic and epigenetic signals and reveals repurposable drug candidates for multiple sclerosis.Human molecular genetics · 2023Article
- Novel genetic resources associated with sucrose and stachyose content through genome-wide association study in soybean (Frontiers in plant science · 2023Article
- Effective Subject Representation based on Multi-omics Disease Networks using Graph Embedding.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022Article
- scGWAS: landscape of trait-cell type associations by integrating single-cell transcriptomics-wide and genome-wide association studies.Genome biology · 2022Article
- Identifying candidate genes and drug targets for Alzheimer's disease by an integrative network approach using genetic and brain region-specific proteomic data.Human molecular genetics · 2022Article
- Article
113 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
motivationAn important question that has emerged from the recent success of genome-wide association studies (GWAS) is how to detect genetic signals beyond single markers/genes in order to explore their combined effects on mediating complex diseases and traits. Integrative testing of GWAS association data with that from prior-knowledge databases and proteome studies has recently gained attention. These methodologies may hold promise for comprehensively examining the interactions between genes underlying the pathogenesis of complex diseases.
methodsHere, we present a dense module searching (DMS) method to identify candidate subnetworks or genes for complex diseases by integrating the association signal from GWAS datasets into the human protein-protein interaction (PPI) network. The DMS method extensively searches for subnetworks enriched with low P-value genes in GWAS datasets. Compared with pathway-based approaches, this method introduces flexibility in defining a gene set and can effectively utilize local PPI information.
resultsWe implemented the DMS method in an R package, which can also evaluate and graphically represent the results. We demonstrated DMS in two GWAS datasets for complex diseases, i.e. breast cancer and pancreatic cancer. For each disease, the DMS method successfully identified a set of significant modules and candidate genes, including some well-studied genes not detected in the single-marker analysis of GWA studies. Functional enrichment analysis and comparison with previously published methods showed that the genes we identified by DMS have higher association signal. AVAILABILITY: dmGWAS package and documents are available at http://bioinfo.mc.vanderbilt.edu/dmGWAS.html.
Indexed as
Identifiers
What OpenQuestion holds
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.