{"doi":"10.1371/journal.pcbi.1011915","title":"Computational prediction of protein interactions in single cells by proximity sequencing","abstract":"Proximity sequencing (Prox-seq) simultaneously measures gene expression, protein expression and protein complexes on single cells. Using information from dual-antibody binding events, Prox-seq infers surface protein dimers at the single-cell level. Prox-seq provides multi-dimensional phenotyping of single cells in high throughput, and was recently used to track the formation of receptor complexes during cell signaling and discovered a novel interaction between CD9 and CD8 in naïve T cells. The distribution of protein abundance can affect identification of protein complexes in a complicated manner in dual-binding assays like Prox-seq. These effects are difficult to explore with experiments, yet important for accurate quantification of protein complexes. Here, we introduce a physical model of Prox-seq and computationally evaluate several different methods for reducing background noise when quantifying protein complexes. Furthermore, we developed an improved method for analysis of Prox-seq data, which resulted in more accurate and robust quantification of protein complexes. Finally, our Prox-seq model offers a simple way to investigate the behavior of Prox-seq data under various biological conditions and guide users toward selecting the best analysis method for their data.","journal":"PLoS Computational Biology","year":2024,"id":467528,"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":0.902,"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":561838,"name":"Hoang Van Phan","orcid":"0000-0002-0162-4283","position":1,"is_corresponding":false},{"id":564548,"name":"Luke Vistain","orcid":"0000-0003-0090-3763","position":2,"is_corresponding":false},{"id":256389,"name":"Mengjie Chen","orcid":"0000-0003-1579-087X","position":3,"is_corresponding":false},{"id":226352,"name":"Aly A. Khan","orcid":"0000-0003-3933-8538","position":4,"is_corresponding":false},{"id":229004,"name":"Savaş Tay","orcid":"0000-0002-1912-6020","position":5,"is_corresponding":false},{"id":1176527,"name":"Junjie Xia","orcid":"0000-0001-9714-7065","position":0,"is_corresponding":true}],"reference_count":14,"raw_metadata":null,"created_at":"2026-07-19T02:05:15.025255Z","pmid":"38483861","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":[]}