{"doi":"10.1093/hmg/ddx043","title":"Conditional eQTL analysis reveals allelic heterogeneity of gene expression","abstract":null,"journal":"Human Molecular Genetics","year":2017,"id":590286,"datarank":5.768073337046439,"base_score":5.123963979403259,"endowment":5.123963979403259,"self_citation_contribution":0.7685945969104889,"citation_network_contribution":4.99947874013595,"self_endowment_contribution":0.7685945969104889,"citer_contribution":4.99947874013595,"corpus_percentile":null,"corpus_rank":null,"citation_count":167,"citer_count":144,"citers_with_citation_signal":132,"citers_with_endowment":132,"datacite_reuse_total":14,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":5234,"name":"Jouke-Jan Hottenga","orcid":null,"position":1,"is_corresponding":false},{"id":5264,"name":"Michel G. Nivard","orcid":"0000-0003-2015-1888","position":2,"is_corresponding":false},{"id":5193,"name":"Abdel Abdellaoui","orcid":"0000-0003-1088-6784","position":3,"is_corresponding":false},{"id":1510333,"name":"Bram Laport","orcid":null,"position":4,"is_corresponding":false},{"id":1510334,"name":"Eco J. de Geus","orcid":null,"position":5,"is_corresponding":false},{"id":103619,"name":"Fred A. Wright","orcid":"0000-0002-8238-6626","position":6,"is_corresponding":false},{"id":5395,"name":"Brenda W.J.H. Penninx","orcid":"0000-0001-7779-9672","position":7,"is_corresponding":false},{"id":5322,"name":"Dorret I. Boomsma","orcid":"0000-0002-7099-7972","position":8,"is_corresponding":false},{"id":5237,"name":"Rick Jansen","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Conditional eQTL analysis reveals allelic heterogeneity of gene expression","abstract":"In recent years, multiple eQTL (expression quantitative trait loci) catalogs have become available that can help understand the functionality of complex trait-related single nucleotide polymorphisms (SNPs). In eQTL catalogs, gene expression is often strongly associated with multiple SNPs, which may reflect either one or multiple independent associations. Conditional eQTL analysis allows a distinction between dependent and independent eQTLs. We performed conditional eQTL analysis in 4,896 peripheral blood microarray gene expression samples. Our analysis showed that 35% of genes with a cis eQTL have at least two independent cis eQTLs; for several genes up to 13 independent cis eQTLs were identified. Also, 12% (671) of the independent cis eQTLs identified in conditional analyses were not significant in unconditional analyses. The number of GWAS catalog SNPs identified as eQTL in the conditional analyses increases with 24% as compared to unconditional analyses. We provide an online conditional cis eQTL mapping catalog for whole blood (https://eqtl.onderzoek.io/), which can be used to lookup eQTLs more accurately than in standard unconditional whole blood eQTL databases.","is_dataset_classified":null,"base_score":5.123963979403259,"endowment":5.123963979403259,"datacite_reuse_total":14,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"28165122","pmcid":"PMC6075455","openalex_id":"https://openalex.org/W2587589680","authors":[],"funders":[{"funder_name":"National Institute of Mental Health","grant_id":"RC2 MH089951","title":null},{"funder_name":"Netherlands Organization for Scientific Research","grant_id":"904-61-090, 985-10-002,904-61-193,480-04-004, 400-05-717, 912-100-20;","title":null},{"funder_name":"Spinozapremie","grant_id":"56-464-14192","title":null},{"funder_name":"Geestkracht program","grant_id":"10-000-1002","title":null},{"funder_name":"Neuroscience Campus Amsterdam and the European Science Council","grant_id":"230374","title":null},{"funder_name":"BBMRI-NL, NWO","grant_id":"184.021.007","title":null},{"funder_name":"Dutch Research Council (NWO)","grant_id":"904-61-090","title":null}],"total_grants":7,"fwci":16.6903,"citation_percentile":0.99373129,"influential_citations":0,"citation_trend":[{"year":2017,"count":13},{"year":2018,"count":20},{"year":2019,"count":25},{"year":2020,"count":21},{"year":2021,"count":25},{"year":2022,"count":17},{"year":2023,"count":16},{"year":2024,"count":14},{"year":2025,"count":12},{"year":2026,"count":4}],"oa_status":"bronze","license":"cc-by","oa_locations":[{"url":"https://academic.oup.com/hmg/article-pdf/26/8/1444/25421187/ddx043.pdf","host_type":"journal"},{"url":"https://academic.oup.com/hmg/article-pdf/26/8/1444/25421187/ddx043.pdf","host_type":"publisher"},{"url":"http://academic.oup.com/hmg/article-pdf/26/8/1444/25421187/ddx043.pdf","host_type":"publisher"},{"url":"https://doi.org/10.1093/hmg/ddx043","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/28165122","host_type":"repository"},{"url":"https://research.vumc.nl/en/publications/52ed72b5-164f-425a-a661-0ea3bb0965ce","host_type":"repository"},{"url":"https://research.vu.nl/en/publications/12fad16e-b1b2-4862-8b01-ddd15970c10f","host_type":"repository"},{"url":"https://pure.amsterdamumc.nl/en/publications/6c533a80-cc39-4630-b961-a977b5f58b10","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6075455","host_type":"repository"},{"url":"https://hdl.handle.net/1871.1/12fad16e-b1b2-4862-8b01-ddd15970c10f","host_type":"repository"},{"url":"https://pure.amsterdamumc.nl/ws/files/158983554/Conditional-eqtl-analysis-reveals-allelic-heterogeneity-of-gene-expression.pdf","host_type":"repository"}],"fields_of_study":["Genetic Associations and Epidemiology","Bioinformatics and Genomic Networks","Gene expression and cancer classification","Alleles","Blood","Gene Expression Profiling","Gene Expression Regulation","Genetic Heterogeneity","Genome-Wide Association Study","Humans","Phenotype","Polymorphism, Single Nucleotide","Quantitative Trait Loci","Transcriptome"],"mesh_terms":["Alleles","Blood","Gene Expression Regulation","Humans","Phenotype","Genetic Heterogeneity","Polymorphism, Single Nucleotide","Gene Expression Profiling","Quantitative Trait Loci","Genome-Wide Association Study","Transcriptome"],"keywords":["Expression quantitative trait loci","Biology","Single-nucleotide polymorphism","Genetics","Quantitative trait locus","Computational biology","Genome-wide association study","Gene","Genetic association","Genotype"],"sdg_mappings":[],"linked_datasets":[{"doi":"10.6084/m9.figshare.14173743.v1","title":"Additional file 12 of Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.14173743","title":"Additional file 12 of Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.14173746.v1","title":"Additional file 1 of Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.14173746","title":"Additional file 1 of Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.14524482.v1","title":"Additional file 1 of MARS: leveraging allelic heterogeneity to increase power of association testing","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.14524482","title":"Additional file 1 of MARS: leveraging allelic heterogeneity to increase power of association testing","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.14524497.v1","title":"Additional file 6 of MARS: leveraging allelic heterogeneity to increase power of association testing","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.14524497","title":"Additional file 6 of MARS: leveraging allelic heterogeneity to increase power of association testing","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.20479722.v1","title":"Additional file 1 of Limited evidence for blood eQTLs in human sexual dimorphism","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.20479722","title":"Additional file 1 of Limited evidence for blood eQTLs in human sexual dimorphism","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.25376120.v1","title":"Additional file 1 of Incorporating genetic similarity of auxiliary samples into eGene identification under the transfer learning framework","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.25376120","title":"Additional file 1 of Incorporating genetic similarity of auxiliary samples into eGene identification under the transfer learning framework","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.25591355.v1","title":"Additional file 1 of Control of false discoveries in grouped hypothesis testing for eQTL data","publisher":"figshare","resource_type":"JournalArticle"},{"doi":"10.6084/m9.figshare.25591355","title":"Additional file 1 of Control of false discoveries in grouped hypothesis testing for eQTL data","publisher":"figshare","resource_type":"JournalArticle"}],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"refsnp"},{"name":"dbgap"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-24T16:06:18.840226Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}