{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T05:49:41Z","timestamp":1782280181022,"version":"3.54.5"},"posted":{"date-parts":[[2024,12,3]]},"group-title":"Bioinformatics","reference-count":43,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T00:00:00Z","timestamp":1733184000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2024,12,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  Differential co-expression analysis (DCA) aims to identify genes in a pathway whose shared expression depends on a risk factor. While DCA provides insights into the biological activity of diseases, existing methods are limited to categorical risk factors and\/or suffer from bias due to batch and variance-specific effects. We propose a new framework, Kernel-based Differential Co-expression Analysis (KDCA), that harnesses correlation patterns between genes in a pathway to detect differential co-expression arising from general (i.e., continuous, discrete, or categorical) risk factors. Using various simulated pathway architectures, we find that KDCA accounts for common sources of bias to control the type I error rate while substantially increasing the power compared to the standard eigengene approach. We then applied KDCA to The Cancer Genome Atlas thyroid data set and found several differentially co-expressed pathways by age of diagnosis and\n                  <jats:italic>BRAF<\/jats:italic>\n                  mutation status that were undetected by the eigengene method. Collectively, our results demonstrate that KDCA is a powerful testing framework that expands DCA applications in expression studies.\n                <\/jats:p>","DOI":"10.1101\/2024.11.29.626006","type":"posted-content","created":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T17:25:38Z","timestamp":1733246738000},"source":"Crossref","is-referenced-by-count":0,"title":["A powerful framework for differential co-expression analysis of general risk factors"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7762-4055","authenticated-orcid":false,"given":"Andrew J.","family":"Bass","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6394-6731","authenticated-orcid":false,"given":"David J.","family":"Cutler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9647-9738","authenticated-orcid":false,"given":"Michael P.","family":"Epstein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2024120512550671000_2024.11.29.626006v1.1","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.40538"},{"key":"2024120512550671000_2024.11.29.626006v1.2","doi-asserted-by":"publisher","DOI":"10.1038\/nrg2502"},{"key":"2024120512550671000_2024.11.29.626006v1.3","doi-asserted-by":"publisher","DOI":"10.1186\/1752-0509-4-136"},{"key":"2024120512550671000_2024.11.29.626006v1.4","doi-asserted-by":"publisher","DOI":"10.1016\/j.cels.2016.11.006"},{"key":"2024120512550671000_2024.11.29.626006v1.5","doi-asserted-by":"publisher","DOI":"10.1186\/s12918-016-0315-y"},{"key":"2024120512550671000_2024.11.29.626006v1.6","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1005153"},{"key":"2024120512550671000_2024.11.29.626006v1.7","doi-asserted-by":"publisher","DOI":"10.1042\/BST0360941"},{"key":"2024120512550671000_2024.11.29.626006v1.8","doi-asserted-by":"publisher","DOI":"10.1016\/j.gene.2012.11.028"},{"key":"2024120512550671000_2024.11.29.626006v1.9","doi-asserted-by":"publisher","DOI":"10.1186\/s12918-016-0349-1"},{"key":"2024120512550671000_2024.11.29.626006v1.10","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-11-497"},{"key":"2024120512550671000_2024.11.29.626006v1.11","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btp502"},{"key":"2024120512550671000_2024.11.29.626006v1.12","doi-asserted-by":"publisher","DOI":"10.1186\/1752-0509-1-54"},{"key":"2024120512550671000_2024.11.29.626006v1.13","doi-asserted-by":"publisher","DOI":"10.1186\/s13073-024-01329-0"},{"key":"2024120512550671000_2024.11.29.626006v1.14","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2014.09.050"},{"key":"2024120512550671000_2024.11.29.626006v1.15","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1989.tb01747.x"},{"key":"2024120512550671000_2024.11.29.626006v1.16","unstructured":"Gretton A , Fukumizu K , Teo C , Song L , Sch\u00f6lkopf B , Smola A. A kernel statistical test of independence. In: Platt J , Koller D , Singer Y , Roweis S , editors. Advances in Neural Information Processing Systems. vol. 20. Curran Associates, Inc.; 2007."},{"issue":"6","key":"2024120512550671000_2024.11.29.626006v1.17","first-page":"2769","article-title":"Measuring and testing dependence by correlation of distances","volume":"35","year":"2007","journal-title":"The Annals of Statistics"},{"key":"2024120512550671000_2024.11.29.626006v1.18","unstructured":"Zhang K , Peters J , Janzing D , Sch\u00f6lkopf B. Kernel-based conditional independence test and application in causal discovery. In: Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence. UAI\u201911. Arlington, Virginia, USA: AUAI Press; 2011. p. 804\u2013813."},{"key":"2024120512550671000_2024.11.29.626006v1.19","first-page":"132","article-title":"Measuring multivariate association and beyond","volume":"10","year":"2016","journal-title":"Statistics Surveys"},{"issue":"5","key":"2024120512550671000_2024.11.29.626006v1.20","first-page":"2263","article-title":"Equivalence of distance-based and RKHS-based statistics in hypothesis testing","volume":"41","year":"2013","journal-title":"The Annals of Statistics"},{"key":"2024120512550671000_2024.11.29.626006v1.21","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12314"},{"key":"2024120512550671000_2024.11.29.626006v1.22","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2007.10.010"},{"key":"2024120512550671000_2024.11.29.626006v1.23","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2010.05.002"},{"key":"2024120512550671000_2024.11.29.626006v1.24","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2011.05.029"},{"key":"2024120512550671000_2024.11.29.626006v1.25","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2016.01.017"},{"key":"2024120512550671000_2024.11.29.626006v1.26","doi-asserted-by":"publisher","DOI":"10.1159\/000312643"},{"key":"2024120512550671000_2024.11.29.626006v1.27","doi-asserted-by":"publisher","DOI":"10.2307\/2346911"},{"key":"2024120512550671000_2024.11.29.626006v1.28","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12684"},{"key":"2024120512550671000_2024.11.29.626006v1.29","doi-asserted-by":"publisher","DOI":"10.1089\/152791601750294344"},{"key":"2024120512550671000_2024.11.29.626006v1.30","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-021-02533-6"},{"issue":"8","key":"2024120512550671000_2024.11.29.626006v1.31","first-page":"e71","article-title":"TCGAbiolinks: an R\/Bioconductor package for integrative analysis of TCGA data","volume":"44","year":"2015","journal-title":"Nucleic Acids Research"},{"key":"2024120512550671000_2024.11.29.626006v1.32","doi-asserted-by":"crossref","unstructured":"Tufano RP , Teixeira GV , Bishop J , Carson KA , Xing M. BRAF mutation in papillary thyroid cancer and its value in tailoring initial treatment: a systematic review and meta-analysis. Medicine. 2012;91(5).","DOI":"10.1097\/MD.0b013e31826a9c71"},{"key":"2024120512550671000_2024.11.29.626006v1.33","doi-asserted-by":"publisher","DOI":"10.1038\/nrc3497"},{"key":"2024120512550671000_2024.11.29.626006v1.34","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-22560-y"},{"key":"2024120512550671000_2024.11.29.626006v1.35","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-019-1700-9"},{"key":"2024120512550671000_2024.11.29.626006v1.36","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0506580102"},{"key":"2024120512550671000_2024.11.29.626006v1.37","doi-asserted-by":"publisher","DOI":"10.1210\/jc.2013-2503"},{"key":"2024120512550671000_2024.11.29.626006v1.38","doi-asserted-by":"publisher","DOI":"10.1186\/s12916-016-0559-9"},{"key":"2024120512550671000_2024.11.29.626006v1.39","doi-asserted-by":"crossref","unstructured":"Zhang Y , Liu Y , Wang L , Song H. The expression and role of trefoil factors in human tumors. Translational Cancer Research. 2019;8(4).","DOI":"10.21037\/tcr.2019.07.48"},{"key":"2024120512550671000_2024.11.29.626006v1.40","doi-asserted-by":"crossref","unstructured":"Popova NV , J\u00fccker M. The functional role of extracellular matrix proteins in cancer. Cancers. 2022;14(1).","DOI":"10.3390\/cancers14010238"},{"key":"2024120512550671000_2024.11.29.626006v1.41","doi-asserted-by":"publisher","DOI":"10.1172\/JCI10905"},{"key":"2024120512550671000_2024.11.29.626006v1.42","doi-asserted-by":"crossref","unstructured":"Abi Nahed R , Safwan-Zaiter H , Gemy K , Lyko C , Boudaud M , Desseux M , et al. The multifaceted functions of prion protein (PrPC) in cancer. Cancers. 2023;15(20).","DOI":"10.3390\/cancers15204982"},{"key":"2024120512550671000_2024.11.29.626006v1.43","doi-asserted-by":"publisher","DOI":"10.1038\/nrc3431"}],"container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.1101\/2024.11.29.626006","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T04:58:15Z","timestamp":1782277095000},"score":1,"resource":{"primary":{"URL":"http:\/\/biorxiv.org\/lookup\/doi\/10.1101\/2024.11.29.626006"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,3]]},"references-count":43,"URL":"https:\/\/doi.org\/10.1101\/2024.11.29.626006","relation":{"is-preprint-of":[{"id-type":"doi","id":"10.1093\/bioinformatics\/btaf565","asserted-by":"subject"}]},"subject":[],"published":{"date-parts":[[2024,12,3]]},"subtype":"preprint"}}