{"doi":"10.1101/2021.08.08.455466","title":"Powerful eQTL mapping through low coverage RNA sequencing","abstract":"ABSTRACT Mapping genetic variants that regulate gene expression (eQTL mapping) in large-scale RNA sequencing (RNA-seq) studies is often employed to understand functional consequences of regulatory variants. However, the high cost of RNA-Seq limits sample size, sequencing depth, and therefore, discovery power. In this work, we demonstrate that, given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample and increasing the number of individuals sequenced in the assay. We perform RNA-Seq of whole blood tissue across 1490 individuals at low-coverage (5.9 million reads/sample) and show that the effective power is higher than that of an RNA-Seq study of 570 individuals at high-coverage (13.9 million reads/sample). Next, we leverage synthetic datasets derived from real RNA-Seq data to explore the interplay of coverage and number individuals in eQTL studies, and show that a 10-fold reduction in coverage leads to only a 2.5-fold reduction in statistical power. Our study suggests that lowering coverage while increasing the number of individuals is an effective approach to increase discovery power in RNA-Seq studies.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2021,"id":217740,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9503,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":815014,"name":"Toni Boltz","orcid":"0000-0003-0226-7924","position":1,"is_corresponding":false},{"id":311857,"name":"Kangcheng Hou","orcid":"0000-0001-7110-5596","position":2,"is_corresponding":false},{"id":815015,"name":"Merel Bot","orcid":"0000-0003-2261-7119","position":3,"is_corresponding":false},{"id":815016,"name":"Chenda Duan","orcid":"0009-0003-8652-3960","position":4,"is_corresponding":false},{"id":478447,"name":"Loes M. Olde Loohuis","orcid":"0000-0002-3327-7837","position":5,"is_corresponding":false},{"id":237625,"name":"Marco P. Boks","orcid":"0000-0001-6163-7484","position":6,"is_corresponding":false},{"id":62374,"name":"René S. Kahn","orcid":"0000-0001-5909-8004","position":7,"is_corresponding":false},{"id":40487,"name":"Roel A. Ophoff","orcid":"0000-0002-8287-6457","position":8,"is_corresponding":false},{"id":731,"name":"Bogdan Paşaniuc","orcid":"0000-0002-0227-2056","position":9,"is_corresponding":false},{"id":311855,"name":"Tommer Schwarz","orcid":"0000-0003-1777-3280","position":0,"is_corresponding":true}],"reference_count":41,"raw_metadata":null,"created_at":"2026-07-18T23:53:24.683898Z","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":[]}