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Identifying rare variants from exome scans: the GAW17 experience
Saurabh Ghosh1, Heike Bickeböller, Julia Bailey
1Human Genetics Unit, Indian Statistical Institute, Kolkata 700018, India. saurabh@isical.ac.in.
BMC Proceedings
|March 1, 2012
Summary
Genetic Analysis Workshop 17 (GAW17) evaluated statistical genetics methods for complex traits. Participants used 1000 Genomes Project data to develop novel approaches for analyzing rare variants.
Area of Science:
- Statistical genetics
- Genomics
- Complex trait analysis
Background:
- Genetic Analysis Workshop 17 (GAW17) convened to address challenges in analyzing complex traits.
- Rare genetic variants play a crucial role in modulating complex diseases.
- Existing statistical genetic methods require evaluation and enhancement for rare variant analysis.
Purpose of the Study:
- To provide an overview of the 1000 Genomes Project exome and simulated phenotype data used in GAW17.
- To outline the diverse analytical issues tackled by GAW17 participants.
- To describe the manuscript preparation process following the workshop discussions.
Main Methods:
- Utilized 1000 Genomes Project exome sequencing data.
- Employed simulated phenotype data for robust statistical analysis.
- Facilitated collaborative analysis and discussion among participants.
Main Results:
- GAW17 successfully provided a platform for method evaluation and development.
- Participants addressed various complex genetic analysis challenges.
- Discussions led to the preparation of multiple manuscripts.
Conclusions:
- GAW17 fostered advancements in statistical genetic methods for rare variants.
- The workshop highlighted the importance of high-quality genomic and phenotype data.
- The collaborative environment facilitated the dissemination of new analytical strategies.
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