{"doi":"10.1093/nargab/lqae138","title":"Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package","abstract":"Understanding cancer mechanisms, defining subtypes, predicting prognosis and assessing therapy efficacy are crucial aspects of cancer research. Gene-expression signatures derived from bulk gene expression data have played a significant role in these endeavors over the past decade. However, recent advancements in high-resolution transcriptomic technologies, such as single-cell RNA sequencing and spatial transcriptomics, have revealed the complex cellular heterogeneity within tumors, necessitating the development of computational tools to characterize tumor mass heterogeneity accurately. Thus we implemented signifinder, a novel R Bioconductor package designed to streamline the collection and use of cancer transcriptional signatures across bulk, single-cell, and spatial transcriptomics data. Leveraging publicly available signatures curated by signifinder, users can assess a wide range of tumor characteristics, including hallmark processes, therapy responses, and tumor microenvironment peculiarities. Through three case studies, we demonstrate the utility of transcriptional signatures in bulk, single-cell, and spatial transcriptomic data analyses, providing insights into cell-resolution transcriptional signatures in oncology. Signifinder represents a significant advancement in cancer transcriptomic data analysis, offering a comprehensive framework for interpreting high-resolution data and addressing tumor complexity.","journal":"NAR Genomics and Bioinformatics","year":2024,"id":443393,"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":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8728,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1257537,"name":"Laura Masatti","orcid":"0009-0002-2610-4265","position":1,"is_corresponding":false},{"id":1258013,"name":"Anna Bortolato","orcid":null,"position":2,"is_corresponding":false},{"id":1257538,"name":"Anna Corrà","orcid":"0009-0002-1937-5120","position":3,"is_corresponding":false},{"id":1257539,"name":"Fabiola Pedrini","orcid":"0009-0002-7302-0486","position":4,"is_corresponding":false},{"id":1258014,"name":"Martina Aere","orcid":null,"position":5,"is_corresponding":false},{"id":1257540,"name":"Giovanni Esposito","orcid":"0000-0003-1019-6476","position":6,"is_corresponding":false},{"id":749590,"name":"Paolo Martini","orcid":"0000-0002-0146-1031","position":7,"is_corresponding":false},{"id":58989,"name":"Davide Risso","orcid":"0000-0001-8508-5012","position":8,"is_corresponding":false},{"id":262173,"name":"Chiara Romualdi","orcid":"0000-0003-4792-9047","position":9,"is_corresponding":false},{"id":1204322,"name":"Enrica Calura","orcid":"0000-0001-8463-2432","position":10,"is_corresponding":false},{"id":1257536,"name":"Stefania Pirrotta","orcid":"0009-0004-0030-217X","position":0,"is_corresponding":true}],"reference_count":51,"raw_metadata":null,"created_at":"2026-07-19T02:01:24.471942Z","pmid":"39363890","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":[]}