Analysis of Sequence Data and Its Implementation Towards Medical Practice

Abstract

The analysis of next generation sequencing data has been recognized as an indispensable step in cancer research. It requires various types of analysis, such as finding somatic mutations like SNV, Indel and structural variations from whole genome or exome sequence data, and aberrant splicing and fusion transcripts from RNA sequence data. We have developed several analysis methods, e.g., somatic mutation caller, called HapMuC, which utilizes germline heterozygous variants near somatic mutation candidates to achieve higher accuracy, finding tandem repeat duplications from exome sequence, and fusion transcripts. Those computer programs have been implemented in the supercomputer system in the Institute of Medical Science, the University of Tokyo. In this talk, we introduce several data analysis methods for next generation sequencing data together with an application of clinical sequencing that Human Genome Center, IMS Hospital, Advanced Clinical Research Center and Health Intelligence Center in our institute have been addressing for familial colorectal cancer and blood disease patients.