{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T12:12:10Z","timestamp":1767183130305},"reference-count":58,"publisher":"Oxford University Press (OUP)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,3,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Selecting a small number of signature genes for accurate classification of samples is essential for the development of diagnostic tests. However, many genes are highly correlated in gene expression data, and hence, many possible sets of genes are potential classifiers. Because treatment outcomes are poor in advanced chronic myeloid leukemia (CML), we hypothesized that expression of classifiers of advanced phase CML when detected in early CML [chronic phase (CP) CML], correlates with subsequent poorer therapeutic outcome.<\/jats:p><jats:p>Results: We developed a method that integrates gene expression data with expert knowledge and predicted functional relationships using iterative Bayesian model averaging. Applying our integrated method to CML, we identified small sets of signature genes that are highly predictive of disease phases and that are more robust and stable than using expression data alone. The accuracy of our algorithm was evaluated using cross-validation on the gene expression data. We then tested the hypothesis that gene sets associated with advanced phase CML would predict relapse after allogeneic transplantation in 176 independent CP CML cases. Our gene signatures of advanced phase CML are predictive of relapse even after adjustment for known risk factors associated with transplant outcomes.<\/jats:p><jats:p>Availability: The source codes and data sets used are available from the web site http:\/\/expression.washington.edu\/publications\/kayee\/integratedBMA.<\/jats:p><jats:p>Contact: \u00a0kayee@u.washington.edu<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts059","type":"journal-article","created":{"date-parts":[[2012,2,2]],"date-time":"2012-02-02T17:01:11Z","timestamp":1328202071000},"page":"823-830","source":"Crossref","is-referenced-by-count":14,"title":["Predicting relapse prior to transplantation in chronic myeloid leukemia by integrating expert knowledge and expression data"],"prefix":"10.1093","volume":"28","author":[{"given":"K. Y.","family":"Yeung","sequence":"first","affiliation":[{"name":"1 Department of Microbiology, University of Washington, Seattle, WA 98195, 2Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 and 3Department of Statistics, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"T. A.","family":"Gooley","sequence":"additional","affiliation":[{"name":"1 Department of Microbiology, University of Washington, Seattle, WA 98195, 2Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 and 3Department of Statistics, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A.","family":"Zhang","sequence":"additional","affiliation":[{"name":"1 Department of Microbiology, University of Washington, Seattle, WA 98195, 2Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 and 3Department of Statistics, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A. E.","family":"Raftery","sequence":"additional","affiliation":[{"name":"1 Department of Microbiology, University of Washington, Seattle, WA 98195, 2Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 and 3Department of Statistics, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J. P.","family":"Radich","sequence":"additional","affiliation":[{"name":"1 Department of Microbiology, University of Washington, Seattle, WA 98195, 2Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 and 3Department of Statistics, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V. G.","family":"Oehler","sequence":"additional","affiliation":[{"name":"1 Department of Microbiology, University of Washington, Seattle, WA 98195, 2Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109 and 3Department of Statistics, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2012,1,31]]},"reference":[{"key":"2023012512201869100_B1","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1093\/bioinformatics\/btp630","article-title":"Robust biomarker identification for cancer diagnosis with ensemble feature selection methods","volume":"26","author":"Abeel","year":"2010","journal-title":"Bioinformatics"},{"key":"2023012512201869100_B2","doi-asserted-by":"crossref","first-page":"6745","DOI":"10.1073\/pnas.96.12.6745","article-title":"Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays","volume":"96","author":"Alon","year":"1999","journal-title":"Proc. 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