High-throughput technologies such as next generation sequencing (NGS) can routinely produce massive amounts of data. These technologies allow us to describe all variants in a genome and international collaborative efforts such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) have begun to catalogue and release data on genomic variation in a variety of cancer types.
However, such datasets pose new challenges in the way the data have to be analyzed, annotated and interpreted which are not trivial and are daunting to the wet-lab biologist. This course covers state-of-the-art and best-practice tools for the analysis of cancer genomes. We describe, and give hands-on experience of, the entire analysis workflow from raw data generated by a sequencing machine to deriving variant calls (SNVs, copy-number and structural variants) that are ready for downstream analysis and interpretation
https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/