1. Genome STRiP ASHG Workshop demo materials
Bob Handsaker
October 19, 2014

2. Running Genome STRiP directly on AWS

3. Cloud demo: Genome STRiP command line
StarCluster
Cloud
Storage
Sequencing data
Amazon
Web Services
Genome STRIP

4. Cloud computing scenarios
Why are people interested in Genome STRiP on the cloud?
Increase compute and storage capacity for large-scale processing
Large genome studies
Economical and with short lead time
Utilize data sets that are stored in the cloud
Public data sets (e.g Genomes)
Data sharing with collaborators
No need to download bulky data to each site

5. Cookbook recipe: Genotyping in 1000 Genomes Phase 1
Inputs
A site VCF file describing the variants (e.g. large deletions) to genotype
Outputs
Genotype VCF file
Plots for quality control
1000 Genomes Data
You choose the BAM file location:
Cached copy on Amazon S3 storage
HTTP from NCBI or EBI
StarCluster
Uses the StarCluster software from MIT for Amazon EC2 provisioning

6. Demo Show input vcf file in local directory
starcluster put gs-cluster example.vcf example.vcf
starcluster sshmaster gs-cluster
./genotype-sites.sh example.vcf run1
(show output)
(log out)
starcluster get gs-cluster run1 run1
Show vcf in textedit
Show genotyping plot pdf

7. Cloud computing support in Genome STRiP
Remote BAM file access
Support for multiple file access protocols in addition to local files
HTTP / HTTPS
FTP
Amazon S3 protocol
Pre-computed metadata for 1000 Genomes Phase 1 and Phase 3
Eliminates the need to run Genome STRiP preprocessing
Avoids the need to download the 1000 Genomes BAM files
Metadata is relatively compact: 5Gb (Phase1) and 13Gb (Phase 3)
ftp://ftp.broadinstitute.org/pub/svtoolkit/public_metadata/
Cookbook recipes for common scenarios
Genotyping variants in 1000 Genomes samples

8. Genome STRiP cookbook

9. Sample genotyping output
Standard VCF file with sample genotypes
##fileformat=VCFv4.1
#CHROM POS ID REF ALT QUAL FILTER INFO FORMAT HG HG00100
DEL_2_ A <DEL> END= GT:FT:GQ 0/0:PASS:71 0/1:PASS:14
Genotyping plot for visual verification
Histogram of normalized read depth
Colors indicate confident calls
(gray samples are below 95% confidence)
Small numbers on plot indicate evidence
from read pairs or split reads

10. Command summary starcluster start gs-cluster -s 1
starcluster put gs-cluster example.vcf example.vcf
starcluster sshmaster gs-cluster
./genotype_sites.sh example.vcf run1
starcluster get gs-cluster run1 run1
starcluster terminate gs-cluster
Launch Amazon compute cluster
Copy input file from local to cloud
Log in to remote cluster
Run genotyping command script
Copy output files from cloud to local
Shut down compute cluster

11. For more information …. Bonus evening session
Tonight (Monday) 6:30 – 8:00 PM
Room 24, Upper Level
Web site
Support forum (Genome STRiP topic in GATK forum)
AWS Support In Genome STRiP
Seva Kashin
Poster 603 T (Tuesday afternoon)
Multi-allelic copy number variation in humans
Early look at upcoming Genome STRiP functionality for duplications and multi-allelic CNVs

13. Intro Slides for Gabor

14. Genome STRiP Genome STRucture in Populations
Integrates multiple features of sequence data with population-based patterns across many individuals
Handsaker, R.E., Korn, J.M., Nemesh, J. & McCarroll, S.A.
Discovery and genotyping of genome structural polymorphism by sequencing on a population scale. Nat Genet 43, (2011)

15. Genome STRiP Structural variation analysis from sequence data
Integrative
Combines multiple feature of the sequence data (read pairs, read depth, split reads)
Integrative approaches have consistently shown higher accuracy
Population-aware
Increases power and accuracy
Particularly important for low-coverage genomes
Modular architecture
Discovery of new variants
Genotyping of newly discovered variants and/or known variants
Includes tools for QC / analysis
Initial prototype developed for analyses in 1000 Genomes Project
Low false discovery rate and high sensitivity

16. Demo Slides