{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T16:32:31Z","timestamp":1764174751068,"version":"3.37.3"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2020,3,13]],"date-time":"2020-03-13T00:00:00Z","timestamp":1584057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01GM122083","P01NS097206","U01MH116441","NS111602"],"award-info":[{"award-number":["R01GM122083","P01NS097206","U01MH116441","NS111602"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Emory University WHSC 2018 Synergy Award"},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P30AG10161","R01AG17917","U01AG61356"],"award-info":[{"award-number":["P30AG10161","R01AG17917","U01AG61356"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,6,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>In the analysis of high-throughput omics data from tissue samples, estimating and accounting for cell composition have been recognized as important steps. High cost, intensive labor requirements and technical limitations hinder the cell composition quantification using cell-sorting or single-cell technologies. Computational methods for cell composition estimation are available, but they are either limited by the availability of a reference panel or suffer from low accuracy.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We introduce TOols for the Analysis of heterogeneouS Tissues TOAST\/-P\u00a0and TOAST\/+P, two partial reference-free algorithms for estimating cell composition of heterogeneous tissues based on their gene expression profiles. TOAST\/-P and TOAST\/+P incorporate additional biological information, including cell-type-specific markers and prior knowledge of compositions, in the estimation procedure. Extensive simulation studies and real data analyses demonstrate that the proposed methods provide more accurate and robust cell composition estimation than existing methods.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The proposed methods TOAST\/-P and TOAST\/+P are implemented as part of the R\/Bioconductor package TOAST at https:\/\/bioconductor.org\/packages\/TOAST.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Contact<\/jats:title>\n                  <jats:p>ziyi.li@emory.edu or hao.wu@emory.edu<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa184","type":"journal-article","created":{"date-parts":[[2020,3,10]],"date-time":"2020-03-10T20:47:02Z","timestamp":1583873222000},"page":"3431-3438","source":"Crossref","is-referenced-by-count":15,"title":["Robust partial reference-free cell composition estimation from tissue expression"],"prefix":"10.1093","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8359-0533","authenticated-orcid":false,"given":"Ziyi","family":"Li","sequence":"first","affiliation":[{"name":"Department of Biostatistics and Bioinformatics , Emory University, Atlanta, GA 30322, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenxing","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Bioinformatics , Emory University, Atlanta, GA 30322, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Cheng","sequence":"additional","affiliation":[{"name":"Institute of Biomedical Research , Yunnan University, Kunming, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6137-6659","authenticated-orcid":false,"given":"Peng","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Human Genetics , Emory University, Atlanta, GA 30322, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Bioinformatics , Emory University, Atlanta, GA 30322, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2020,3,13]]},"reference":[{"key":"2023062300081359300_btaa184-B1","doi-asserted-by":"crossref","first-page":"e6098","DOI":"10.1371\/journal.pone.0006098","article-title":"Deconvolution of blood microarray data identifies cellular activation patterns in systemic lupus erythematosus","volume":"4","author":"Abbas","year":"2009","journal-title":"PLoS One"},{"key":"2023062300081359300_btaa184-B2","doi-asserted-by":"crossref","first-page":"S161","DOI":"10.3233\/JAD-179939","article-title":"Religious orders study and rush memory and aging project","volume":"64","author":"Bennett","year":"2018","journal-title":"J. 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