{"database":"GEO","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Other":["ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE339nnn/GSE339457/"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"omics_type":["Transcriptomics"],"species":["Homo sapiens"],"gds_type":["Expression profiling by high throughput sequencing"],"full_dataset_link":["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE339457"],"repository":["GEO"],"entry_type":["GSE"],"additional_accession":[]},"is_claimable":false,"name":"Mapping transcriptional responses to cellular perturbation dictionaries with RNA fingerprinting [scRNA-Seq]","description":"Single-cell perturbation dictionaries systematically measure how cells respond to genetic and chemical perturbations, creating the opportunity to assign causal interpretations to observational data. We introduce RNA fingerprinting, a statistical framework that maps transcriptional responses from new experiments onto reference perturbation dictionaries. RNA fingerprinting learns representations of perturbations, or ``fingerprints,\" from single-cell data, then probabilistically assigns query cells to one or more candidate perturbations. We benchmark our method across ground-truth datasets, demonstrating accurate assignments at single-cell resolution, scalability to genome-wide screens, and the ability to resolve combinatorial perturbations. We demonstrate its broad utility across diverse biological settings: identifying context-specific regulators of p53 under ribosomal stress, characterizing drug mechanisms of action and dose-dependent off-target effects, and uncovering cytokine-driven B cell heterogeneity during secondary influenza infection in vivo. Together, these results establish RNA fingerprinting as a versatile framework for interpreting single-cell datasets by linking cellular states to the underlying perturbations which generated them.","dates":{"publication":"2026/07/27"},"accession":"GSE339457","cross_references":{"GSM":["GSM9895960","GSM9895959","GSM9895961"],"GPL":["18573"],"GSE":["339457"],"taxon":["Homo sapiens"]}}