{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Song B"],"funding":["NHGRI NIH HHS","NCI NIH HHS","National Science Foundation (NSF)","U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI)","NIGMS NIH HHS","U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)","U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS)"],"pagination":["493-504"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11906366"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["27(3)"],"pubmed_abstract":["Understanding how cells respond differently to perturbation is crucial in cell biology, but existing methods often fail to accurately quantify and interpret heterogeneous single-cell responses. Here we introduce the perturbation-response score (PS), a method to quantify diverse perturbation responses at a single-cell level. Applied to single-cell perturbation datasets such as Perturb-seq, PS outperforms existing methods in quantifying partial gene perturbations. PS further enables single-cell dosage analysis without needing to titrate perturbations, and identifies 'buffered' and 'sensitive' response patterns of essential genes, depending on whether their moderate perturbations lead to strong downstream effects. PS reveals differential cellular responses on perturbing key genes in contexts such as T cell stimulation, latent HIV-1 expression and pancreatic differentiation. Notably, we identified a previously unknown role for the coiled-coil domain containing 6 (CCDC6) in regulating liver and pancreatic cell fate decisions. PS provides a powerful method for dose-to-function analysis, offering deeper insights from single-cell perturbation data."],"journal":["Nature cell biology"],"pubmed_title":["Decoding heterogeneous single-cell perturbation responses."],"pmcid":["PMC11906366"],"funding_grant_id":["R35 GM140888","UM1HG012654, U01HG012051","R35GM140888","P30 CA008748","R01HG010753","UM1 HG012654","DBI-1846216, DMS-2113754","R01HL168174"],"pubmed_authors":["Chao L","Kale HT","Song B","Untermoser N","Zhang H","Dai W","McMyn NF","Song D","Yang D","Rosen B","Cheng X","Siliciano JD","Krejci A","Williams B","Burckstummer T","Li W","Diao Y","Vasilyev A","Wang Q","Huangfu D","Loregger A","Siliciano RF","Liu D","Li JJ"],"additional_accession":[]},"is_claimable":false,"name":"Decoding heterogeneous single-cell perturbation responses.","description":"Understanding how cells respond differently to perturbation is crucial in cell biology, but existing methods often fail to accurately quantify and interpret heterogeneous single-cell responses. Here we introduce the perturbation-response score (PS), a method to quantify diverse perturbation responses at a single-cell level. Applied to single-cell perturbation datasets such as Perturb-seq, PS outperforms existing methods in quantifying partial gene perturbations. PS further enables single-cell dosage analysis without needing to titrate perturbations, and identifies 'buffered' and 'sensitive' response patterns of essential genes, depending on whether their moderate perturbations lead to strong downstream effects. PS reveals differential cellular responses on perturbing key genes in contexts such as T cell stimulation, latent HIV-1 expression and pancreatic differentiation. Notably, we identified a previously unknown role for the coiled-coil domain containing 6 (CCDC6) in regulating liver and pancreatic cell fate decisions. PS provides a powerful method for dose-to-function analysis, offering deeper insights from single-cell perturbation data.","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Mar","modification":"2026-06-02T16:20:42.322Z","creation":"2025-04-04T00:06:27.108Z"},"accession":"S-EPMC11906366","cross_references":{"pubmed":["40011559"],"doi":["10.1038/s41556-025-01626-9"]}}