Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM
Howard Hughes Medical Institute · University of California, Santa Cruz
Abstract
MOTIVATION: High-throughput data is providing a comprehensive view of the molecular changes in cancer tissues. New technologies allow for the simultaneous genome-wide assay of the state of genome copy number variation, gene expression, DNA methylation and epigenetics of tumor samples and cancer cell lines. Analyses of current data sets find that genetic alterations between patients can differ but often involve common pathways. It is therefore critical to identify relevant pathways involved in cancer progression and detect how they are altered in different patients. RESULTS: We present a novel method for inferring patient-specific genetic activities incorporating curated pathway interactions among genes. A gene…
Citation impact
- FWCI
- 16.88
- Percentile
- 100%
- References
- 51
Authors
8- CVCharles VaskeCorresponding
Howard Hughes Medical Institute, University of California, Santa Cruz
- SCStephen C. Benz
Howard Hughes Medical Institute, University of California, Santa Cruz
- ZSZack Sanborn
Howard Hughes Medical Institute, University of California, Santa Cruz
- DEDent Earl
Howard Hughes Medical Institute, University of California, Santa Cruz
- CSChristopher Szeto
Howard Hughes Medical Institute, University of California, Santa Cruz
Topics & keywords
- Computational biology
- Inference
- Genomics
- Epigenetics
- Biology
- DNA methylation
- False positive paradox
- Gene