{"doi":"10.1101/2025.08.07.669008","title":"Comparative evaluation of genomic footprinting algorithms for predicting transcription factor binding sites in single-cell data","abstract":"SUMMARY Transcription factors (TFs) have millions of potential binding sites across the human genome, but only a fraction are bound in a given context. Genomic footprinting aims to identify context-specific binding sites by detecting patterns in open chromatin data. While powerful, these approaches face technical challenges, especially in single-cell applications. We developed a benchmarking framework for cell-type specific footprinting and used it to evaluate the consistency, reproducibility, and equivalency of three leading methods across data quality scenarios and as a function of cell-type similarity. Peak-level read coverage emerged as the strongest predictor of stable footprints. Motivated by limited reproducibility across tools, we built an ensemble model that improved concordance with ChIP-seq. To encourage broader adoption and continued tool development, we provide practical guidelines for robust genomic footprinting in single-cell datasets and a roadmap for extracting deeper insights about how gene regulatory networks vary across cell types in complex tissues.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":558760,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9449,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":21349,"name":"Sean Whalen","orcid":"0000-0002-6648-3610","position":1,"is_corresponding":false},{"id":21361,"name":"Katherine S. Pollard","orcid":"0000-0002-9870-6196","position":2,"is_corresponding":false},{"id":461001,"name":"Amanda Everitt","orcid":"0000-0001-9720-1922","position":0,"is_corresponding":true}],"reference_count":60,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:55:30.312295Z","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":[]}