{"doi":"10.1101/gr.272203.120","title":"Profiling the quantitative occupancy of myriad transcription factors across conditions by modeling chromatin accessibility data","abstract":"Over a thousand different transcription factors (TFs) bind with varying occupancy across the human genome. Chromatin immunoprecipitation (ChIP) can assay occupancy genome-wide, but only one TF at a time, limiting our ability to comprehensively observe the TF occupancy landscape, let alone quantify how it changes across conditions. We developed TF occupancy profiler (TOP), a Bayesian hierarchical regression framework, to profile genome-wide quantitative occupancy of numerous TFs using data from a single chromatin accessibility experiment (DNase- or ATAC-seq). TOP is supervised, and its hierarchical structure allows it to predict the occupancy of any sequence-specific TF, even those never assayed with ChIP. We used TOP to profile the quantitative occupancy of hundreds of sequence-specific TFs at sites throughout the genome and examined how their occupancies changed in multiple contexts: in approximately 200 human cell types, through 12 h of exposure to different hormones, and across the genetic backgrounds of 70 individuals. TOP enables cost-effective exploration of quantitative changes in the landscape of TF binding.","journal":"Genome Research","year":2022,"id":300196,"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":0.6707,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":571756,"name":"Jianling Zhong","orcid":null,"position":1,"is_corresponding":false},{"id":515165,"name":"Alexias Safi","orcid":"0000-0001-6381-4923","position":2,"is_corresponding":false},{"id":571757,"name":"Linda K. Hong","orcid":null,"position":3,"is_corresponding":false},{"id":16397,"name":"Alok K. Tewari","orcid":"0000-0003-2617-7499","position":4,"is_corresponding":false},{"id":11660,"name":"Lingyun Song","orcid":"0000-0003-2271-8067","position":5,"is_corresponding":false},{"id":27827,"name":"Timothy E. Reddy","orcid":"0000-0002-7629-061X","position":6,"is_corresponding":false},{"id":570800,"name":"Li Ma","orcid":"0000-0002-0159-3296","position":7,"is_corresponding":false},{"id":5210,"name":"Gregory E. Crawford","orcid":"0000-0001-6106-2772","position":8,"is_corresponding":false},{"id":12940,"name":"Alexander J. Hartemink","orcid":"0000-0002-1292-2606","position":9,"is_corresponding":false},{"id":498178,"name":"Kaixuan Luo","orcid":"0000-0003-1515-5737","position":0,"is_corresponding":true}],"reference_count":65,"raw_metadata":null,"created_at":"2026-07-19T00:31:53.559757Z","pmid":"35609992","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":[]}