講演情報
[PE5-2]Tumor-GRaPPLer: Integrated analysis of tumor and matched non-tumor tissue from whole genome sequencing data
○Johnson Todd A., Hidewaki Nakagawa (RIKEN Center for Integrative Medical Sciences, Laboratory for Cancer Genomics, Yokohama, Japan)
Whole genome sequence analysis of tumor and matched non-tumor tissue provides a rich source of information for identifying pathogenic germline and somatic small single nucleotide and insertion-deletion variants as well as more complex structural variants (SVs) and copy-number alterations (CNAs). Various pipelines have been developed for performing the primary WGS data analysis, but few are integrated with downstream tertiary analyses, such as CNA frequency analysis, mutational or copy-number signatures, or neoantigen identification. Towards that goal, we have developed Tumor-GRaPPLer, which utilizes software from the Hartwig Medical Foundation and colleagues for the primary WGS analysis, produces a concise Excel file summarizing sample purity, ploidy, and quality controls, candidate driver variants (small variants + CNAs/SVs), and extracted worksheets of germline and somatic variants that have an annotated impact on protein coding sequences. VCFs with all somatic variants and other output are transformed into R data.tables for easy searching and filtering. Currently, Tumor-GRaPPLer includes workflows for CNA frequency analysis across tumor sub-types and Circos plot generation, data reformatting and scripts for running GISTIC 2, CNApp, and maftools, mutational signature analysis with SigProfiler, and extraction and annotation of coding variant and gene fusion data for neoantigen identification using pVACtools. Tumor-GRaPPLer is available at https://github.com/toddajohnson/tumor-grappler.