dc.contributor.author | Park, Yongjin P. | |
dc.contributor.author | Kellis, Manolis | |
dc.date.accessioned | 2022-05-18T15:41:51Z | |
dc.date.available | 2021-11-01T14:33:55Z | |
dc.date.available | 2022-05-18T15:41:51Z | |
dc.date.issued | 2021-08 | |
dc.date.submitted | 2021-01 | |
dc.identifier.issn | 1474-760X | |
dc.identifier.uri | https://hdl.handle.net/1721.1/136872.2 | |
dc.description.abstract | Abstract
Finding a causal gene is a fundamental problem in genomic medicine. We present a causal inference framework, CoCoA-diff, that prioritizes disease genes by adjusting confounders without prior knowledge of control variables in single-cell RNA-seq data. We demonstrate that our method substantially improves statistical power in simulations and real-world data analysis of 70k brain cells collected for dissecting Alzheimer’s disease. We identify 215 differentially regulated causal genes in various cell types, including highly relevant genes with a proper cell type context. Genes found in different types enrich distinctive pathways, implicating the importance of cell types in understanding multifaceted disease mechanisms. | en_US |
dc.publisher | Springer Science and Business Media LLC | en_US |
dc.relation.isversionof | https://doi.org/10.1186/s13059-021-02438-4 | en_US |
dc.rights | Creative Commons Attribution | en_US |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
dc.source | BioMed Central | en_US |
dc.title | CoCoA-diff: counterfactual inference for single-cell gene expression analysis | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Genome Biology. 2021 Aug 17;22(1):228 | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | |
dc.relation.journal | Genome Biology | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2021-08-22T03:11:05Z | |
dc.language.rfc3066 | en | |
dc.rights.holder | The Author(s) | |
dspace.date.submission | 2021-08-22T03:11:05Z | |
mit.journal.volume | 22 | en_US |
mit.journal.issue | 1 | en_US |
mit.license | PUBLISHER_CC | |
mit.metadata.status | Authority Work Needed | en_US |