In this webcast on February 19th, Gabe Rudy, Vice President of Product Development, will showcase publicly available databases and resources available for interpreting rare and novel mutations in the context of his own personal exome obtained through a limited 23andMe pilot in 2012.
The last couple years have seen many changes in well-established resources such as OMIM and dbSNP, while motivating new efforts such as ClinVar and PhenoDB to bring NGS interpretation to clinical grade through a global data sharing effort.
In this webcast, Gabe will cover:
The changing landscape of public annotations: Then, Now, and Soon.
Will the new human reference (GRCh38) released in December be a game changer?
Specific examples of improvements in annotation and algorithms that result in more accurate analysis of his own exome.
The utility and progress of NGS to different clinical applications in terms of public resources: carrier screening, hereditary cancer risk, pharmacogenomics, oncology care, and genetic disorder diagnosis.
Sharing of new clinical data: How both variation and phenotype level data is currently being shared and what will be the way forward to match rare and undiagnosed cases at a global scale.
Forensic Biology & Its biological significance.pdf
Using Public Access Clinical Databases to Interpret NGS Variants
1. Using Public Access
Clinical Databases to
Interpret NGS
Variants
February 19, 2014
Gabe Rudy
VP Product Development
Golden Helix
2. Use the Questions pane in
your GoToWebinar window
Questions during
the presentation
3. My Background
Golden Helix
- Founded in 1998
- Genetic association software
- Analytic services
- Hundreds of users worldwide
- Over 800 customer citations in scientific
journals
Products I Build with My Team
- SNP & Variation Suite (SVS)
- SNP, CNV, NGS tertiary analysis
- Import and deal with all flavors of upstream data
- GenomeBrowse
- Visualization of everything with genomic coordinates.
All standardized file formats.
- RNA-Seq Pipeline
- Expression profiling bioinformatics
4. Agenda
Getting High Quality Variant Calls
Data Sharing and the Maturing of Public Resources
2
3
4
Clinical Grade Candidate Variant Identification
How I Met My Exomes1
NGS Clinical Utopia: Are We There Yet?5
5. Exome Sequencing in Consumer Genomics
Exomes done as part of Pilot
Program
80x coverage
Raw data with no interpretation
Erin
JIA
Gabe
(me)
Ethan
6. Research or clinical grade?
Total Reads 140M
Unique Align 87%
Mean Target 105x
% Target at 2x 97%
% Target at 10x 94%
% Target at 20x 89%
% Target at 30x 83%
7. Agenda
Getting High Quality Variant Calls
Data Sharing and the Maturing of Public Resources
2
3
4
Clinical Grade Candidate Variant Identification
How I Met My Exomes1
NGS Clinical Utopia: Are We There Yet?5
8. Alignment and Variant Calling Broken Down
2012 2 VCFs from
23andMe
- BWA 0.6.1
- GATK (early & late 2012)
2013 Real Time Genomics
- v3.1.2 2013-05-02
- Called on Trio
2014 Rerun
- BWA 0.7.6 (2014-01-31)
- FreeBayes
2014 -
BWA/
FreeBayes
16. Agenda
Getting High Quality Variant Calls
Data Sharing and the Maturing of Public Resources
2
3
4
Clinical Grade Candidate Variant Identification
How I Met My Exomes1
NGS Clinical Utopia: Are We There Yet?5
17. Baylor Workflow - Clinical Exomes Paper
Disease gene related
Medically actionable
deleterious variants
Deleterious variants in ACMG
gene list
Deleterious variants
VUS in dominant gene or
homozygous in recessive
gene
Deleterious variant in gene
with no known disease
21. Agenda
Getting High Quality Variant Calls
Data Sharing and the Maturing of Public Resources
2
3
4
Clinical Grade Candidate Variant Identification
How I Met My Exomes1
NGS Clinical Utopia: Are We There Yet?5
22. Applications of NGS Data in the Clinic
Carrier screening –
prenatal and standard
Lifetime risk prediction
Genetic disorder
diagnostics
Oncology care
PGx – dosage and
care
23. ClinVar
Submitters:
- OMIM: Johns Hopkins
- Samuels
- Lab for Molecular Medicine
- Invitae
- Emory Genetics Lab
Star rating system
- 0-4 stars – level of review
ClinVar is designed to provide a freely accessible,
public archive of reports of the relationships
among human variations and phenotypes, with
supporting evidence.
24. HGMD
Data mines academic
papers for reported
functional variants
Also takes
submissions,
corrections reviewed by
team
First available in 1996
- Originally 10k variants
- 105k in Public (2014)
- 148k in “Pro” (2014)
28. BRCA: The back door to Myriad’s database
1995 – Patent issued
to Myriad Genetics
June 2013 – Patents
invalidated by ruling
Lab setting up Dx
has a lot of catch up
“Free the Data” and
other ways in which
Mryiad’s data is in
ClinVar, etc.
Sharing Clinical Reports Project
29. ClinVitae: ClinVar and Friends by Invitae
Sources:
- ClinVar (62,913)
- Emory (13,365)
- ARUP (2,850)
- Carver Mut (199)
- K Cunningham (581)
79,907 V, 9,189 G
- 32,523 Pathogenic
- 38,796 Likely Pathogenic
Provided in HGVS
- 59,878 after mapping to genomic space
31. Agenda
Getting High Quality Variant Calls
Data Sharing and the Maturing of Public Resources
2
3
4
Clinical Grade Candidate Variant Identification
How I Met My Exomes1
NGS Clinical Utopia: Are We There Yet?5
32. Training
Most variants are rare or novel
- Training to interpret these is
extensive
MD/Pathology background is
insufficient
Need a PhD in molecular
genetics
There’s only 500 board certified
Clinical Molecular Geneticists
since started
Let’s share in the learning
process
Baylor Exome Sign-Out
33. Thank you
Heidi Rehm – Chief Laboratory Director at
Laboratory for Molecular Medicine,
PCPGM
Joel Parker – Cancer Genetics, UNC
Chapel Hill
Gerry Higgins – VP, Pharmacogenomic
Science, Assure Rx Health
Frank Schacherer – Chief Technical
Officer, BIOBASE
Reece Hart – Computational Biologist,
Invitae
Greta Linse Peterson – Director of Product
Management and Quality, Golden Helix
36. Phenotypeing and Matchmaking Portals
PhenoDB
PhenomeCentral.org
Orphanet – Resources on over
6000 rare diseases and orphan
drugs.
European centric:
- GEN2PHEN (G2P)
37. Updated VCF and report at end of October
GATK is a Research Tool. Clinics Beware.
38. Rare Disease Resources
Rare defined as affecting fewer
than 200k people.
- Most affect fewer than 6000
- 25M Americans have a rare disease
NIH Genetic and Rare Diseases
Information Center (GARD)
ClinicalTrials.gov
Orphanet – Resources on over
6000 rare diseases and orphan
drugs.
39. Cancer Resources
Behind germline because:
- Sharing cancer data is more wholesale.
You don’t just post a variant + a
phenotype, you have to have whole
variant sets
- Cohorts are not covering enough ethnic
groups. African americans under-
represented
- Not a lot of incentive for large cancer
centers to share their internal
databases
What do we do with the data?
- 70% of tumors can find driver genes.
But not many have actionable drugs.
- Need much more evidence based trials
to find more examples like BRAF
V600E
Pic of BRAF V600E and drug