A consortium of leading informatics laboratories at Harvard, MIT, and BU, supported by a grant from the National Library of Medicine.
Next Generation Sequencing
In this course, Next Generation Sequencing (NGS), students will learn about NGS technologies as well as computational and annotation tools for conducting practical genome-wide analysis and interpretation of NGS data. Furthermore, the promise of personalized medicine and the applications and implications of NGS in clinical settings will be discussed.
This course consists of three learning modules. Three main lecturers (Peter J. Park, PhD; Dennis P. Wall, PhD; and Peter J. Tonellato, PhD) and three guest lecturers (Peter V. Kharchenko, PhD; Mark S. Boguski, MD, PhD, FCAP; and George M. Church, PhD) present:
Module I: NGS - Technologies and Design
Gain basic knowledge of NGS technologies and platforms and develop an understanding of important aspects of NGS studies, including coverage and depth of sequencing, base calling and quality scores, and sources of error. Learn about NGS applications, including RNA-seq, ChIP-seq, and other functional sequencing assays.
Module II: NGS - Data Analysis and Computation
Become familiar with methods and tools for high-throughput computational analysis of NGS data, including alignment and annotation tools, and the advantages of using cloud and grid computing for NGS data analysis.
Module III: NGS - Clinical Applications and Implications
Acquire knowledge of disease association studies, cancer genomics, personalized medicine, and clinical implications of NGS.
Introduce basic functions and applications of valuable NGS data analysis tools through live demonstrations. Gain hands-on experience by performing exercises with GenomeQuest, a software platform for processing and analyzing NGS data, and Ingenuity Pathways Analysis (IPA), a pathways analysis software application.