DawnRank: discovering personalized driver genes in cancer

Abstract

Large-scale cancer genomic studies have revealed that the genetic heterogeneity of the same type of cancer is greater than previously thought. A key question in cancer genomics is the identification of driver genes. Although existing methods have identified many common drivers, it remains challenging to predict personalized drivers to assess rare and even patient-specific mutations. We developed a new algorithm called DawnRank to directly prioritize altered genes on a single patient level. Applications to TCGA datasets demonstrated the effectiveness of our method. We believe DawnRank complements existing driver identification methods and will help us discover personalized causal mutations that would otherwise be obscured by tumor heterogeneity. Source code can be accessed at http://bioen-compbio.bioen.illinois.edu/DawnRank/.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-014-0056-8) contains supplementary material, which is available to authorized users.

Gastric cancer and gene copy number variation: emerging cancer drivers for targeted therapy

“…152 In comparison, the DawnRank algorithm was designated to identify personalized driver genes in cancer. 153 Along with the expansion in cancer genomic datasets and continuous improvement of data-mining methods, the identification of cancer-driver genes may bring enormous therapeutic opportunities in the future.…”

Somatic gene copy number alterations in colorectal cancer: new quest for cancer drivers and biomarkers

“…Even with these advances, the main challenging is distinguishing the alterations that play causative roles (drivers) from the random alterations that accumulate during colorectal carcinogenesis (passengers). 18 Integrating these identified CNA regions and functional knowledge about the affected genes would help understanding the relative importance of different genes in CRC initiation and progression. For uncharacterized genes, the extent or significance of its CNA alteration is often used to judge its relevance to cancer.…”

iCAGES: integrated CAncer GEnome Score for comprehensively prioritizing driver genes in personal cancer genomes

“…While other personalized cancer driver prioritization tools, such as DawnRank [21], often require patient’s cancer signature data, including genomic mutation, tumor gene expression data, and normal gene expression data, iCAGES only requires the patient’s genomic mutation data (in VCF format or in ANNOVAR input format) and handles all data preprocessing steps for users. Nevertheless, iCAGES users can optionally supply structural variant information (deletion/duplication), gene expression information (over/under-expressed), or cancer subtype information (for more accurate Phenolyzer analysis) to potentially improve predictions.…”

“…Some tools, such as PARADIGM-SHIFT [20], DawnRank [21], OncoIMPACT[22], and ActiveDriver [23], provide personal cancer driver gene prediction. However, they require gene expression, phosphorylation, or copy number variation data from patients, all of which are not often feasible to obtain due to cost and other practical issues.…”