{"doi":"10.1101/2020.01.25.919738","title":"Transcription factor enrichment analysis (TFEA): Quantifying the activity of hundreds of transcription factors from a single experiment","abstract":"1 Abstract Detecting differential activation of transcription factors (TFs) in response to perturbation provides insight into cellular processes. Transcription Factor Enrichment Analysis (TFEA) is a robust and reliable computational method that detects differential activity of hundreds of TFs given any set of perturbation data. TFEA draws inspiration from GSEA and detects positional motif enrichment within a list of ranked regions of interest (ROIs). As ROIs are typically inferred from the data, we also introduce muMerge , a statistically principled method of generating a consensus list of ROIs from multiple replicates and conditions. TFEA is broadly applicable to data that informs on transcriptional regulation including nascent (eg. PRO-Seq), CAGE, ChIP-Seq, and accessibility (e.g. ATAC-Seq). TFEA not only identifies the key regulators responding to a perturbation, but also temporally unravels regulatory networks with time series data. Consequently, TFEA serves as a hypothesis-generating tool that provides an easy, rigorous, and cost-effective means to broadly assess TF activity yielding new biological insights.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2020,"id":120239,"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":11,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9399,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":557259,"name":"Jacob T. Stanley","orcid":"0000-0002-5652-727X","position":1,"is_corresponding":false},{"id":557260,"name":"Rutendo F. Sigauke","orcid":"0000-0001-5882-4377","position":2,"is_corresponding":false},{"id":277785,"name":"Cecilia B. Levandowski","orcid":"0000-0001-6809-4048","position":3,"is_corresponding":false},{"id":277787,"name":"Zachary L. Maas","orcid":"0009-0008-5645-2811","position":4,"is_corresponding":false},{"id":417050,"name":"Jessica Westfall","orcid":null,"position":5,"is_corresponding":false},{"id":226578,"name":"Dylan J. Taatjes","orcid":"0000-0003-4444-5688","position":6,"is_corresponding":false},{"id":28295,"name":"Robin D. Dowell","orcid":"0000-0001-7665-9985","position":7,"is_corresponding":false},{"id":277789,"name":"Jonathan D. Rubin","orcid":"0000-0003-1129-2910","position":0,"is_corresponding":true}],"reference_count":64,"raw_metadata":null,"created_at":"2026-07-18T23:14:33.640077Z","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":[]}