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Genomic analyses of hundreds of prostate tumors have defined a diverse landscape of mutations and genome rearrangements, but the transcriptomic effect of this complexity is less well understood, particularly at the individual tumor level. We selected a cohort of 25 high-risk prostate tumors, representing the lethal phenotype, and applied deep RNA-sequencing(More)
A key challenge in cancer genomics is the identification and prioritization of genomic aberrations that potentially act as drivers of cancer. In this paper we introduce HIT’nDRIVE, a combinatorial method to identify aberrant genes that can collectively influence possibly distant “outlier” genes based on what we call the “random-walk facility location”(More)
Prioritizing molecular alterations that act as drivers of cancer remains a crucial bottleneck in therapeutic development. Here we introduce HIT'nDRIVE, a computational method that integrates genomic and transcriptomic data to identify a set of patient-specific, sequence-altered genes, with sufficient collective influence over dysregulated transcripts.(More)
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