{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T01:16:28Z","timestamp":1768007788961,"version":"3.49.0"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"20","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":2272,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,10,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Tissue heterogeneity, arising from multiple cell types, is a major confounding factor in experiments that focus on studying cell types, e.g. their expression profiles, in isolation. Although sample heterogeneity can be addressed by manual microdissection, prior to conducting experiments, computational treatment on heterogeneous measurements have become a reliable alternative to perform this microdissection in silico. Favoring computation over manual purification has its advantages, such as time consumption, measuring responses of multiple cell types simultaneously, keeping samples intact of external perturbations and unaltered yield of molecular content.<\/jats:p>\n               <jats:p>Results: We formalize a probabilistic model, DSection, and show with simulations as well as with real microarray data that DSection attains increased modeling accuracy in terms of (i) estimating cell-type proportions of heterogeneous tissue samples, (ii) estimating replication variance and (iii) identifying differential expression across cell types under various experimental conditions. As our reference we use the corresponding linear regression model, which mirrors the performance of the majority of current non-probabilistic modeling approaches.<\/jats:p>\n               <jats:p>Availability and Software: All codes are written in Matlab, and are freely available upon request as well as at the project web page http:\/\/www.cs.tut.fi\/\u223cerkkila2\/. Furthermore, a web-application for DSection exists at http:\/\/informatics.systemsbiology.net\/DSection.<\/jats:p>\n               <jats:p>Contact: \u00a0timo.p.erkkila@tut.fi; harri.lahdesmaki@tut.fi<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq406","type":"journal-article","created":{"date-parts":[[2010,7,15]],"date-time":"2010-07-15T02:49:54Z","timestamp":1279162194000},"page":"2571-2577","source":"Crossref","is-referenced-by-count":66,"title":["Probabilistic analysis of gene expression measurements from heterogeneous tissues"],"prefix":"10.1093","volume":"26","author":[{"given":"Timo","family":"Erkkil\u00e4","sequence":"first","affiliation":[{"name":"1 Department of Signal Processing, Tampere University of Technology, Finland, 2Institute for Systems Biology, Seattle, WA, USA, 3Institute of Medical Technology, University of Tampere and Tampere University Hospital and 4Department of Information and Computer Science, Helsinki University of Technology, Finland"},{"name":"1 Department of Signal Processing, Tampere University of Technology, Finland, 2Institute for Systems Biology, Seattle, WA, USA, 3Institute of Medical Technology, University of Tampere and Tampere University Hospital and 4Department of Information and Computer Science, Helsinki University of Technology, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saara","family":"Lehmusvaara","sequence":"additional","affiliation":[{"name":"1 Department of Signal Processing, Tampere University of Technology, Finland, 2Institute for Systems Biology, Seattle, WA, USA, 3Institute of Medical Technology, University of Tampere and Tampere University Hospital and 4Department of Information and Computer Science, Helsinki University of Technology, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pekka","family":"Ruusuvuori","sequence":"additional","affiliation":[{"name":"1 Department of Signal Processing, Tampere University of Technology, Finland, 2Institute for Systems Biology, Seattle, WA, USA, 3Institute of Medical Technology, University of Tampere and Tampere University Hospital and 4Department of Information and Computer Science, Helsinki University of Technology, Finland"},{"name":"1 Department of Signal Processing, Tampere University of Technology, Finland, 2Institute for Systems Biology, Seattle, WA, USA, 3Institute of Medical Technology, University of Tampere and Tampere University Hospital and 4Department of Information and Computer Science, Helsinki University of Technology, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tapio","family":"Visakorpi","sequence":"additional","affiliation":[{"name":"1 Department of Signal Processing, Tampere University of Technology, Finland, 2Institute for Systems Biology, Seattle, WA, USA, 3Institute of Medical Technology, University of Tampere and Tampere University Hospital and 4Department of Information and Computer Science, Helsinki University of Technology, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ilya","family":"Shmulevich","sequence":"additional","affiliation":[{"name":"1 Department of Signal Processing, Tampere University of Technology, Finland, 2Institute for Systems Biology, Seattle, WA, USA, 3Institute of Medical Technology, University of Tampere and Tampere University Hospital and 4Department of Information and Computer Science, Helsinki University of Technology, Finland"},{"name":"1 Department of Signal Processing, Tampere University of Technology, Finland, 2Institute for Systems Biology, Seattle, WA, USA, 3Institute of Medical Technology, University of Tampere and Tampere University Hospital and 4Department of Information and Computer Science, Helsinki University of Technology, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Harri","family":"L\u00e4hdesm\u00e4ki","sequence":"additional","affiliation":[{"name":"1 Department of Signal Processing, Tampere University of Technology, Finland, 2Institute for Systems Biology, Seattle, WA, USA, 3Institute of Medical Technology, University of Tampere and Tampere University Hospital and 4Department of Information and Computer Science, Helsinki University of Technology, Finland"},{"name":"1 Department of Signal Processing, Tampere University of Technology, Finland, 2Institute for Systems Biology, Seattle, WA, USA, 3Institute of Medical Technology, University of Tampere and Tampere University Hospital and 4Department of Information and Computer Science, Helsinki University of Technology, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2010,7,14]]},"reference":[{"key":"2023012507535865300_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":"2023012507535865300_B2"},{"key":"2023012507535865300_B3","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1020281327116","article-title":"An introduction to mcmc for machine learning","volume":"50","author":"Andrieu","year":"2003","journal-title":"Mach. Learn."},{"key":"2023012507535865300_B4","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1080\/01621459.1996.10476956","article-title":"Markov chain monte carlo convergence diagnostics: a comparative review","volume":"91","author":"Cowles","year":"1996","journal-title":"J. Am. Stat. Assoc."},{"key":"2023012507535865300_B5","doi-asserted-by":"crossref","first-page":"922","DOI":"10.1214\/09-AOAS236","article-title":"Are a set of microarrays independent of each other?","volume":"3","author":"Efron","year":"2009","journal-title":"Ann. Appl. Stat."},{"key":"2023012507535865300_B6","doi-asserted-by":"crossref","first-page":"998","DOI":"10.1126\/science.274.5289.998","article-title":"Laser capture microdissection","volume":"274","author":"Emmert-Buck","year":"1996","journal-title":"Science"},{"key":"2023012507535865300_B7","volume-title":"Bayesian Data Analysis.","author":"Gelman","year":"2004"},{"key":"2023012507535865300_B8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1214\/06-BA117A","article-title":"Prior distributions for variance parameters in hierarchical models","volume":"1","author":"Gelman","year":"2006","journal-title":"Bayesian Anal."},{"key":"2023012507535865300_B9","doi-asserted-by":"crossref","first-page":"3328","DOI":"10.1093\/bioinformatics\/btm508","article-title":"Electronically subtracting expression patterns from a mixed cell population","volume":"23","author":"Gosink","year":"2007","journal-title":"Bioinformatics"},{"key":"2023012507535865300_B10","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1093\/biomet\/82.4.711","article-title":"Reversible jump Markov chain monte carlo computation and bayesian model determination","volume":"82","author":"Green","year":"1995","journal-title":"Biometrika"},{"key":"2023012507535865300_B11","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1186\/1471-2105-7-369","article-title":"Robust computational reconstitution - a new method for the comparative analysis of gene expression in tissues and isolated cell fractions","volume":"7","author":"Hoffmann","year":"2006","journal-title":"BMC Bioinformatics"},{"key":"2023012507535865300_B12","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1093\/biostatistics\/4.2.249","article-title":"Exploration, normalization, and summaries of high density oligonucleotide array probe level data","volume":"4","author":"Irizarry","year":"2003","journal-title":"Biostatistics"},{"key":"2023012507535865300_B13","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1055\/s-0038-1634118","article-title":"Deconfounding microarray analysis - independent measurements of cell type proportions used in a regression model to resolve tissue heterogeneity bias","volume":"45","author":"Jacobsen","year":"2006","journal-title":"Methods Inf. Med."},{"key":"2023012507535865300_B14","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1186\/1756-9966-28-5","article-title":"Tissue microarray analysis of eif4e and its downstream effector proteins in human breast cancer","volume":"28","author":"Kleiner","year":"2009","journal-title":"J. Exp. Clin. Cancer Res."},{"key":"2023012507535865300_B15","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1186\/1471-2105-6-54","article-title":"In silico microdissection of microarray data from heterogeneous cell populations","volume":"6","author":"L\u00e4hdesm\u00e4ki","year":"2005","journal-title":"BMC Bioinformatics"},{"key":"2023012507535865300_B16","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.1101\/gr.079558.108","article-title":"RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays","volume":"18","author":"Marioni","year":"2008","journal-title":"Genome Res."},{"key":"2023012507535865300_B17","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1038\/nmeth.1226","article-title":"Mapping and quantifying mammalian transcriptomes by RNA-seq","volume":"5","author":"Mortazavi","year":"2008","journal-title":"Nat. Methods"},{"key":"2023012507535865300_B18","doi-asserted-by":"crossref","first-page":"2300","DOI":"10.1021\/pr7007626","article-title":"A framework for the automated analysis of subcellular patterns in human protein atlas images","volume":"7","author":"Newberg","year":"2008","journal-title":"J. Proteome Res."},{"key":"2023012507535865300_B19","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1080\/00365510601046334","article-title":"Correlating purity by microdissection with gene expression in gastric cancer tissue","volume":"67","author":"Otsuka","year":"2007","journal-title":"Scand. J. Clin. Lab. Invest."},{"issue":"Suppl.","key":"2023012507535865300_B20","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1038\/ng1032","article-title":"Microarray data normalization and transformation","volume":"32","author":"Quackenbush","year":"2002","journal-title":"Nat. Genet."},{"key":"2023012507535865300_B21","doi-asserted-by":"crossref","first-page":"2882","DOI":"10.1093\/bioinformatics\/btp378","article-title":"Isolate: a computational strategy for identifying the primary origin of cancers using high-throughput sequencing","volume":"25","author":"Quon","year":"2009","journal-title":"Bioinformatics"},{"key":"2023012507535865300_B22","first-page":"554","article-title":"The infinite gaussian mixture model","volume":"12","author":"Rasmussen","year":"2000","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"2023012507535865300_B23","volume-title":"Gaussian Processes for Machine Learning.","author":"Rasmussen","year":"2006"},{"key":"2023012507535865300_B24","doi-asserted-by":"crossref","DOI":"10.2202\/1544-6115.1027","article-title":"Linear models and empirical Bayes methods for assessing differential expression in microarray experiments","volume":"3","author":"Smyth","year":"2004","journal-title":"Stat. Appl. Genet. Mol. Biol."},{"key":"2023012507535865300_B25","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1177\/1066896908316902","article-title":"A novel method of obtaining prostate tissue for gene expression profiling","volume":"17","author":"Sooriakumaran","year":"2009","journal-title":"Int. J. Surg. Pathol."},{"key":"2023012507535865300_B26","doi-asserted-by":"crossref","first-page":"2142","DOI":"10.1002\/pmic.200700199","article-title":"A high-throughput strategy for protein profiling in cell microarrays using automated image analysis","volume":"7","author":"Str\u00f6mberg","year":"2007","journal-title":"Proteomics"},{"key":"2023012507535865300_B27","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1073\/pnas.2536479100","article-title":"In silico dissection of cell-type-associated patterns of gene expression in prostate cancer","volume":"101","author":"Stuart","year":"2004","journal-title":"Proc. Natl Acad. Sci. USA"},{"issue":"Suppl. 1","key":"2023012507535865300_B28","doi-asserted-by":"crossref","first-page":"S279","DOI":"10.1093\/bioinformatics\/17.suppl_1.S279","article-title":"Separation of samples into their constituents using gene expression data","volume":"17","author":"Venet","year":"2001","journal-title":"Bioinformatics"},{"key":"2023012507535865300_B29","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1038\/nrg2484","article-title":"RNA-seq: a revolutionary tool for transcriptomics","volume":"10","author":"Wang","year":"2009","journal-title":"Nat. Rev. Genet."},{"key":"2023012507535865300_B30","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.ymeth.2009.03.016","article-title":"RNA-seq-quantitative measurement of expression through massively parallel rna-sequencing","volume":"48","author":"Wilhelm","year":"2009","journal-title":"Methods"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/20\/2571\/48851523\/bioinformatics_26_20_2571.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/20\/2571\/48851523\/bioinformatics_26_20_2571.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T07:54:37Z","timestamp":1674633277000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/26\/20\/2571\/193363"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,7,14]]},"references-count":30,"journal-issue":{"issue":"20","published-print":{"date-parts":[[2010,10,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btq406","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2010,10,15]]},"published":{"date-parts":[[2010,7,14]]}}}