{"doi":"10.1177/09622802221094133","title":"Unbiased and robust analysis of co-localization in super-resolution images","abstract":"Spatial data from high-resolution images abound in many scientific disciplines. For example, single-molecule localization microscopy, such as stochastic optical reconstruction microscopy, provides super-resolution images to help scientists investigate co-localization of proteins and hence their interactions inside cells, which are key events in living cells. However, there are few accurate methods for analyzing co-localization in super-resolution images. The current methods and software are prone to produce false-positive errors and are restricted to only 2-dimensional images. In this paper, we develop a novel statistical method to effectively address the problems of unbiased and robust quantification and comparison of protein co-localization for multiple 2- and 3-dimensional image datasets. This method significantly improves the analysis of protein co-localization using super-resolution image data, as shown by its excellent performance in simulation studies and an analysis of co-localization of protein light chain 3 and lysosomal-associated membrane protein 1 in cell autophagy. Moreover, this method is directly applicable to co-localization analyses in other disciplines, such as diagnostic imaging, epidemiology, environmental science, and ecology.","journal":"Statistical Methods in Medical Research","year":2022,"id":282174,"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":7,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8796,"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":243966,"name":"Clifford S. Guy","orcid":null,"position":1,"is_corresponding":false},{"id":273878,"name":"Emilio Boada-Romero","orcid":"0000-0003-2482-076X","position":2,"is_corresponding":false},{"id":225738,"name":"Douglas R. Green","orcid":"0000-0002-7332-1417","position":3,"is_corresponding":false},{"id":93,"name":"Margaret E. Flanagan","orcid":"0009-0008-7078-3545","position":4,"is_corresponding":false},{"id":957789,"name":"Cheng Cheng","orcid":"0000-0003-4200-1856","position":5,"is_corresponding":false},{"id":110363,"name":"Hui Zhang","orcid":"0000-0001-6825-5649","position":6,"is_corresponding":false},{"id":842331,"name":"Xueyan Liu","orcid":"0000-0001-8365-5675","position":0,"is_corresponding":true}],"reference_count":25,"raw_metadata":null,"created_at":"2026-07-19T00:29:15.734856Z","pmid":"35450486","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":[]}