What is the Personal Cancer Genome Reporter (PCGR)?

The Personal Cancer Genome Reporter (PCGR) is a stand-alone software package for functional annotation and translation of individual cancer genomes for precision cancer medicine. It interprets both somatic SNVs/InDels and copy number aberrations. The software extends basic gene and variant annotations from the Ensembl’s Variant Effect Predictor (VEP) with oncology-relevant, up-to-date annotations retrieved flexibly through vcfanno. Variants are classified into tiers of clinical significance, and interactive HTML output reports permits exploration of the final results.

Example views from the dashboard HTML output:


The Personal Cancer Genome Reporter has been developed by scientists affiliated with the Norwegian Cancer Genomics Consortium, at the Institute for Cancer Research/Oslo University Hospital.

Example reports

(to view the rmarkdown-based reports, simply remove .flexdb. in the file names for the flexdashboard reports)

Why use PCGR?

The great complexity of acquired mutations in individual tumor genomes poses a severe challenge for clinical interpretation. 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. PCGR integrates a comprehensive set of knowledge resources related to tumor biology and therapeutic biomarkers, both at the gene and variant level. The application generates a tiered report that will aid the interpretation of individual cancer genomes in a clinical setting.

If you use PCGR, please cite our publication:

Sigve Nakken, Ghislain Fournous, Daniel Vodák, Lars Birger Aaasheim, Ola Myklebost, and Eivind Hovig. Personal Cancer Genome Reporter: variant interpretation report for precision oncology (2017). Bioinformatics. 34(10):1778–1780. doi:10.1093/bioinformatics/btx817

Docker-based technology

The PCGR workflow is developed using the Docker technology. The software is thus packaged into isolated containers, in which the installation of all software libraries/tools and required dependencies have been taken care of. In addition to the bundled software, in the form of a Docker image, the workflow only needs to be attached with an annotation data bundle for precision oncology.