Abstract:
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In order to characterize functional consequences of DNA alterations in tumors, we proposed an integrative analysis tool iProFun to screen for DNA alterations perturbing proteogenomic functional traits. We consider multi-omic molecular quantitative traits simultaneously (e.g. mRNA, protein, and phosphoprotein abundances), and aim to identify genes whose DNA alterations have cis-associations with either some or all omic traits. In comparison with analyzing each molecular trait separately, the joint modeling of multi-omics data enjoys enhanced power and it also achieves better accuracy in inferring cis-associations unique to certain type(s) of molecular trait(s). We applied iProFun to clear cell renal carcinoma, and identified we identified DNA alterations preserving through transcriptional, translational, and post-translational levels (cis-effect cascades), and prioritized gene targets for tumor initiation and progression.
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