The Cancer Genome Computational Analysis (CGCA) group — a central component of the ӳý’s Cancer Program — addresses unanswered questions of cancer biology and genomics through the development of computational methods and tools, in conjunction with platforms, datasets and resources. Specifically, the group works to understand cancer by characterizing and interpreting genomic data:
A comprehensive mutational dataset comprising exome mutation data from 21 cancer types
User-friendly, web-based entry point to downloadable TCGA datasets, summary reports, and graphical tools. FireBrowse sits atop TCGA GDAC Firehose, an application providing access to TCGA datasets and a robust selection of tools and pipelines for analyzing cancer genome data, as well as thousands of data analysis archives.
ABSOLUTE can estimate purity/ploidy, and from that compute absolute copy-number and mutation multiplicities.
