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Numerous methods have been developed to solve this problem under various assumptions, but the statistical properties of these methods are often unknown. For example, some widely used methods are reported to output very large subnetworks that are difficult to interpret biologically. In this work, we formulate the identification of altered subnetworks as the problem of estimating the parameters of a class of probability distributions that we call the Altered Subset Distribution (ASD). We derive a connection between a popular method, jActiveModules, and the maximum likelihood estimator (MLE) of the ASD. We show that the MLE is\n                    <jats:italic toggle=\"yes\">statistically biased<\/jats:italic>\n                    , explaining the large subnetworks output by jActiveModules. Based on these insights, we introduce NetMix, an algorithm that uses Gaussian mixture models to obtain less biased estimates of the parameters of the ASD. We demonstrate that NetMix outperforms existing methods in identifying altered subnetworks on both simulated and real data, including the identification of differentially expressed genes from both microarray and RNA-seq experiments and the identification of cancer driver genes in somatic mutation data.\n                  <\/jats:p>","DOI":"10.1089\/cmb.2020.0435","type":"journal-article","created":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T14:00:40Z","timestamp":1609855240000},"page":"469-484","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":10,"title":["NetMix: A Network-Structured Mixture Model for Reduced-Bias Estimation of Altered Subnetworks"],"prefix":"10.1177","volume":"28","author":[{"given":"Matthew A.","family":"Reyna","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, Emory University, Atlanta, Georgia, USA."}]},{"given":"Uthsav","family":"Chitra","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Princeton University, Princeton, New Jersey, USA."}]},{"given":"Rebecca","family":"Elyanow","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Princeton University, Princeton, New Jersey, USA."},{"name":"Department of Computer Science, Brown University, Providence, Rhode Island, USA."}]},{"given":"Benjamin J.","family":"Raphael","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Princeton University, Princeton, New Jersey, USA."}]}],"member":"179","published-online":{"date-parts":[[2021,5,20]]},"reference":[{"key":"e_1_3_6_2_1","doi-asserted-by":"publisher","DOI":"10.1214\/10-AOS817"},{"key":"e_1_3_6_3_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0104993"},{"key":"e_1_3_6_4_1","doi-asserted-by":"publisher","DOI":"10.1214\/10-AOS839"},{"key":"e_1_3_6_5_1","doi-asserted-by":"publisher","DOI":"10.1214\/07-AOS526"},{"key":"e_1_3_6_6_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2017.1286240"},{"key":"e_1_3_6_7_1","doi-asserted-by":"publisher","DOI":"10.1214\/009053605000000787"},{"key":"e_1_3_6_8_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13637-015-0025-6"},{"key":"e_1_3_6_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.060"},{"key":"e_1_3_6_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41540-017-0007-2"},{"key":"e_1_3_6_11_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrg3433"},{"key":"e_1_3_6_12_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.283.5400.381"},{"key":"e_1_3_6_13_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.2355"},{"key":"e_1_3_6_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.copbio.2016.04.007"},{"key":"e_1_3_6_15_1","doi-asserted-by":"publisher","DOI":"10.1214\/16-STS578"},{"key":"e_1_3_6_16_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-016-0989-x"},{"key":"e_1_3_6_17_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1002820"},{"key":"e_1_3_6_18_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1006121"},{"key":"e_1_3_6_19_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btl145"},{"key":"e_1_3_6_20_1","doi-asserted-by":"publisher","DOI":"10.1038\/nprot.2007.324"},{"key":"e_1_3_6_21_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrg.2017.38"},{"key":"e_1_3_6_22_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.3440"},{"key":"e_1_3_6_23_1","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkt1102"},{"key":"e_1_3_6_24_1","doi-asserted-by":"publisher","DOI":"10.1186\/1752-0509-6-92"},{"key":"e_1_3_6_25_1","unstructured":"Daskalakis C. 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