{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T18:58:20Z","timestamp":1768417100822,"version":"3.49.0"},"reference-count":9,"publisher":"Oxford University Press (OUP)","issue":"17","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Gene expression data are typically generated from heterogeneous biological samples that are composed of multiple cell or tissue types, in varying proportions, each contributing to global gene expression. This heterogeneity is a major confounder in standard analysis such as differential expression analysis, where differences in the relative proportions of the constituent cells may prevent or bias the detection of cell-specific differences. Computational deconvolution of global gene expression is an appealing alternative to costly physical sample separation techniques and enables a more detailed analysis of the underlying biological processes at the cell-type level. To facilitate and popularize the application of such methods, we developed CellMix, an R package that incorporates most state-of-the-art deconvolution methods, into an intuitive and extendible framework, providing a single entry point to explore, assess and disentangle gene expression data from heterogeneous samples.<\/jats:p>\n               <jats:p>Availability and Implementation: The CellMix package builds on R\/BioConductor and is available from http:\/\/web.cbio.uct.ac.za\/\u223crenaud\/CRAN\/web\/CellMix. It is currently being submitted to BioConductor. The package\u2019s vignettes notably contain additional information, examples and references.<\/jats:p>\n               <jats:p>Contact: \u00a0renaud@cbio.uct.ac.za<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt351","type":"journal-article","created":{"date-parts":[[2013,7,4]],"date-time":"2013-07-04T07:00:34Z","timestamp":1372921234000},"page":"2211-2212","source":"Crossref","is-referenced-by-count":173,"title":["CellMix: a comprehensive toolbox for gene expression deconvolution"],"prefix":"10.1093","volume":"29","author":[{"given":"Renaud","family":"Gaujoux","sequence":"first","affiliation":[{"name":"1 Computational Biology Group, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, South Africa and 2School of Mathematics, Statistics and Applied Mathematics, National University of Ireland Galway, Ireland"}]},{"given":"Cathal","family":"Seoighe","sequence":"additional","affiliation":[{"name":"1 Computational Biology Group, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, South Africa and 2School of Mathematics, Statistics and Applied Mathematics, National University of Ireland Galway, Ireland"}]}],"member":"286","published-online":{"date-parts":[[2013,7,3]]},"reference":[{"key":"2023012810463380800_btt351-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":"2023012810463380800_btt351-B2","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1186\/1471-2105-12-258","article-title":"Cell subset prediction for blood genomic studies","volume":"12","author":"Bolen","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"2023012810463380800_btt351-B4","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1186\/1471-2105-11-367","article-title":"A flexible R package for nonnegative matrix factorization","volume":"11","author":"Gaujoux","year":"2010","journal-title":"BMC bioinformatics"},{"key":"2023012810463380800_btt351-B5","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1016\/j.meegid.2011.08.014","article-title":"Semi-supervised nonnegative matrix factorization for gene expression deconvolution: a case study","volume":"12","author":"Gaujoux","year":"2012","journal-title":"Infect. 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