{"doi":"10.1016/j.patter.2023.100817","title":"Generative modeling of single-cell gene expression for dose-dependent chemical perturbations","abstract":"Single-cell sequencing reveals the heterogeneity of cellular response to chemical perturbations. However, testing all relevant combinations of cell types, chemicals, and doses is a daunting task. A deep generative learning formalism called variational autoencoders (VAEs) has been effective in predicting single-cell gene expression perturbations for single doses. Here, we introduce single-cell variational inference of dose-response (scVIDR), a VAE-based model that predicts both single-dose and multiple-dose cellular responses better than existing models. We show that scVIDR can predict dose-dependent gene expression across mouse hepatocytes, human blood cells, and cancer cell lines. We biologically interpret the latent space of scVIDR using a regression model and use scVIDR to order individual cells based on their sensitivity to chemical perturbation by assigning each cell a \"pseudo-dose\" value. We envision that scVIDR can help reduce the need for repeated animal testing across tissues, chemicals, and doses.","journal":"Patterns","year":2023,"id":322803,"datarank":0.5533319181170905,"base_score":3.6888794541139363,"endowment":3.6888794541139363,"self_citation_contribution":0.5533319181170905,"citation_network_contribution":0.0,"self_endowment_contribution":0.5533319181170905,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":39,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9489,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":163022,"name":"Rance Nault","orcid":"0000-0002-6822-4962","position":1,"is_corresponding":false},{"id":991006,"name":"David Filipovic","orcid":"0000-0003-4421-1654","position":2,"is_corresponding":false},{"id":991007,"name":"Daniel Marri","orcid":"0000-0002-7109-1566","position":3,"is_corresponding":false},{"id":299063,"name":"Tim Zacharewski","orcid":"0000-0002-3662-7919","position":4,"is_corresponding":false},{"id":299062,"name":"Sudin Bhattacharya","orcid":"0000-0002-2360-1672","position":5,"is_corresponding":false},{"id":991005,"name":"Omar Kana","orcid":"0000-0002-7772-4694","position":0,"is_corresponding":true}],"reference_count":80,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T01:07:47.432636Z","pmid":"37602218","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":[]}