RT Journal Article
SR Electronic
T1 Personal Cancer Genome Reporter: variant interpretation report for precision oncology
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 122366
DO 10.1101/122366
A1 Sigve Nakken
A1 Ghislain Fournous
A1 Daniel Vodák
A1 Lars Birger Aasheim
A1 Ola Myklebost
A1 Eivind Hovig
YR 2017
UL http://biorxiv.org/content/early/2017/08/11/122366.abstract
AB Summary Individual tumor genomes pose a major challenge for clinical interpretation due to their unique sets of acquired mutations. There is a general scarcity of tools that can i) systematically interrogate cancer genomes in the context of diagnostic, prognostic, and therapeutic biomarkers, ii) prioritize and highlight the most important findings, and iii) present the results in a format accessible to clinical experts. We have developed a stand-alone, open-source software package for somatic variant annotation that integrates a comprehensive set of knowledge resources related to tumor biology and therapeutic biomarkers, both at the gene and variant level. Our application generates a tiered report that will aid the interpretation of individual cancer genomes in a clinical setting.Availability and Implementation The software is implemented in Python/R, and is freely available through Docker technology. Documentation, example reports, and installation instructions are accessible via the project GitHub page: https://github.com/sigven/pcgr)Contact sigven{at}ifi.uio.no