This workshop will cover basics of exome-seq analysis including downstream interpretation of variants using a variety of open-source and commercial webtools (Golden Helix, IGV, Ingenuity Variant Analysis, GeneGrid (Genomatix), MuPit/Cravat).
Day 1 – AM (9:30-12:30) Introductory Lectures
(Chunhua Yan, PhD – CBIIT)
- Next generation sequencing technology
- Exome sequencing (Cost, Speed, Gene coverage, Biological implication)
- Experimental design (Sample size, Coverage, Sample submission)
- Mutation Calling (Dream challenge, Genome in Bottle)
(Chih-Hao Hsu, PhD – CBIIT)
- Mutation call software overview and algorithms
- Databases (1000 genomes, ClinVar, cBio, …)
(Li Jia, MSc – CCBR)
- Lessons learned from experimental design
- Best practices in CCBR workflow (includes the discussion on the benchmark, GATK and others used in the tech dev)
- Annovar annotation and filtering
- How to collaborate with CCBR – guide to success
Day 1 – PM (1:30-4:30)
(Bryce Christensen PhD – Golden Helix)
Day 2 – AM (9:30-12:30)
(Susan Dombrowski, PhD – Genomatix)
Day 2 – PM (1:30-4:30) CRAVAT/MuPIT – Analysis of Genomic Variants
(Michael Ryan – Johns Hopkins University)
CRAVAT (www.cravat.us) is a free tool for high-throughput analysis of sequencing variants. CRAVAT is funded by NCI’s Informatics Technology for Cancer Research program. CRAVAT accepts very large variant data files and returns a wide variety of annotations and scores that help with identification of important variants. CRAVAT is a cancer focused analysis package tailored to the needs of cancer studies. The workshop will provide some background on CRAVAT and lots of hands-on exercises to learn how to use the tool and interpret the results.
MuPIT (mupit.icm.jhu) is a sister tool to CRAVAT that shows mutations on 3D protein structures. Clusters of mutations in 3D space are not always apparent from the position of mutations on a protein sequence. For proteins with solved structures, MuPIT can show the position of mutations from your study along with a variety of structural annotations (e.g. the position of a DNA binding site). MuPIT also includes a pre-built database of TCGA mutations so an investigator’s mutations can be viewed in the context of mutations and mutation clusters from other cancer studies. The focus of the workshop will be a series of exercises to learn how to visualize your mutations in MuPIT, how CRAVAT and MuPIT are integrated, and how to manipulate, investigate, and understand the results.