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Genome in a Bottle
GIAB 2013
Workgroup 4: Performance Metrics
Q1.What performance metrics can/should
be generated when someone sequences
the GIAB RMs?
Sequence group 1: Initial characterization of the RM to
develop the ‘truth set’
EVERYTHING!
Chris Mason
Sequence group 2: People using reference materials to
benchmark tests.
Probably Not
Much
To do list:
Create a document describing metadata we want to capture (Chris Mason)
Identify fields we can reliably get from sequencers (Chris Mason)
Develop a flat data structure to capture information (Brad Chapman)
Help develop an improved individual genotype reporting format.
Work with CDC group on this.
Work with VCF/gVCF/GVF developers
✔
Q2. How should performance be
subdivided by region?
Q3. How should performance be
subdivided by variant type?
Assembly Region Reproducibility Track (for all RMs)
Highly confident regions
Less confident regions
Regions we can’t reliably call
NA12878 high quality genotype calls
Focus on SNVs and small indels first
Expand to other variant types as we get more confidence
Update definitions as we add additional reference materials.
Q4. How can GIAB help coordinate
the different groups developing
performance metrics?
Develop APIs for existing software:
X-prize/Harvard School of Public Health software
BCBio variation (comparison software)
O8 (visualization)
BCBio NextGen (Pipeline for running comparison)
Chris Mason’s software suite
Arvados software
GCAT software (Bioplanet)
GeT-RM browser for visualization

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Aug2013 performance metrics working group

  • 1. Genome in a Bottle GIAB 2013 Workgroup 4: Performance Metrics
  • 2. Q1.What performance metrics can/should be generated when someone sequences the GIAB RMs?
  • 3. Sequence group 1: Initial characterization of the RM to develop the ‘truth set’ EVERYTHING!
  • 5. Sequence group 2: People using reference materials to benchmark tests. Probably Not Much
  • 6. To do list: Create a document describing metadata we want to capture (Chris Mason) Identify fields we can reliably get from sequencers (Chris Mason) Develop a flat data structure to capture information (Brad Chapman) Help develop an improved individual genotype reporting format. Work with CDC group on this. Work with VCF/gVCF/GVF developers ✔
  • 7. Q2. How should performance be subdivided by region? Q3. How should performance be subdivided by variant type?
  • 8. Assembly Region Reproducibility Track (for all RMs) Highly confident regions Less confident regions Regions we can’t reliably call NA12878 high quality genotype calls Focus on SNVs and small indels first Expand to other variant types as we get more confidence Update definitions as we add additional reference materials.
  • 9. Q4. How can GIAB help coordinate the different groups developing performance metrics?
  • 10. Develop APIs for existing software: X-prize/Harvard School of Public Health software BCBio variation (comparison software) O8 (visualization) BCBio NextGen (Pipeline for running comparison) Chris Mason’s software suite Arvados software GCAT software (Bioplanet) GeT-RM browser for visualization