{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T23:29:50Z","timestamp":1787009390813,"version":"build-2736575974"},"reference-count":56,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2021,6,22]],"date-time":"2021-06-22T00:00:00Z","timestamp":1624320000000},"content-version":"vor","delay-in-days":74,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["MH108728"],"award-info":[{"award-number":["MH108728"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"CHOP Research Institute"},{"name":"Alavi-Dabiri Postdoctoral Fellowship Award"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,4,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The importance of cell type-specific gene expression in disease-relevant tissues is increasingly recognized in genetic studies of complex diseases. However, most gene expression studies are conducted on bulk tissues, without examining cell type-specific expression profiles. Several computational methods are available for cell type deconvolution (i.e.\u00a0inference of cellular composition) from bulk RNA-Seq data, but few of them impute cell type-specific expression profiles. We hypothesize that with external prior information such as single cell RNA-seq and population-wide expression profiles, it can be computationally tractable to estimate both cellular composition and cell type-specific expression from bulk RNA-Seq data. Here we introduce CellR, which addresses cross-individual gene expression variations to adjust the weights of cell-specific gene markers. It then transforms the deconvolution problem into a linear programming model while taking into account inter\/intra cellular correlations and uses a multi-variate stochastic search algorithm to estimate the cell type-specific expression profiles. Analyses on several complex diseases such as schizophrenia, Alzheimer\u2019s disease, Huntington\u2019s disease and type 2 diabetes validated the efficiency of CellR, while revealing how specific cell types contribute to different diseases. In summary, CellR compares favorably against competing approaches, enabling cell type-specific re-analysis of gene expression data on bulk tissues in complex diseases.<\/jats:p>","DOI":"10.1093\/nargab\/lqab056","type":"journal-article","created":{"date-parts":[[2021,6,22]],"date-time":"2021-06-22T12:41:48Z","timestamp":1624365708000},"source":"Crossref","is-referenced-by-count":7,"title":["A computational method for direct imputation of cell type-specific expression profiles and cellular compositions from bulk-tissue RNA-Seq in brain disorders"],"prefix":"10.1093","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3327-699X","authenticated-orcid":false,"given":"Abolfazl","family":"Doostparast\u00a0Torshizi","sequence":"first","affiliation":[{"name":"Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children\u2019s Hospital of Philadelphia, Philadelphia, PA 19104, USA"},{"name":"Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jubao","family":"Duan","sequence":"additional","affiliation":[{"name":"Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA"},{"name":"Department of Psychiatry and Behavioral Neurosciences, The University of Chicago, Chicago, IL 60015, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5585-982X","authenticated-orcid":false,"given":"Kai","family":"Wang","sequence":"additional","affiliation":[{"name":"Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children\u2019s Hospital of Philadelphia, Philadelphia, PA 19104, USA"},{"name":"Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,6,22]]},"reference":[{"key":"2021070810414472300_B1","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1038\/s41588-018-0129-5","article-title":"Genetic identification of brain cell types underlying schizophrenia","volume":"50","author":"Skene","year":"2018","journal-title":"Nat. Genet."},{"key":"2021070810414472300_B2","doi-asserted-by":"crossref","first-page":"10370","DOI":"10.1073\/pnas.1832361100","article-title":"Expression deconvolution: a reinterpretation of DNA microarray data reveals dynamic changes in cell populations","volume":"100","author":"Lu","year":"2003","journal-title":"Proc. Natl. 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