Quality Control Genotype Calling and Study Design for 1000 Genomes Project

University Of Michigan At Ann Arbor, Ann Arbor MI

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Abstract

DESCRIPTION: (provided by applicant): The 1000 Genomes Project aims to achieve a nearly complete catalog of common human genetic variants by generating high-quality sequence data surveying the genomes of >1000 individuals. This catalog will include SNPs, copy number variants, and short insertion and deletion polymorphisms. By cataloging and describing the relationships between these variants, the Project will provide important benefits to genetic association studies of complex disease. Specifically, availability of very complete lists of candidate functional variants will: (a) accelerate fine-mapping efforts in gene regions indentified through genome-wide association studies or candidate gene studies;(b) improve the power of future genetic association studies by enabling design of next generation genotyping microarrays that more fully represent human genetic variation, and (c) enhance the analysis of ongoing and already completed association studies by improving our ability to "impute" or "predict" untyped genetic variants. This application supports the execution of several tasks essential to the completion of the 1000 Genomes Project. Specifically, we propose working with production centers to finalize the design of the project (for example, by deciding the depth of sequencing required for each individual that is examined or the read length and insert size for the associated sequencing libraries) and to evaluate the trade-offs from different choices of individuals to sequence;we also propose to monitor the data generated to provide regular summaries of data quality and to identify problems with sample tracking before data is released;finally, we will help generate genotype and haplotype calls and prepare submissions of project results to public databases. We believe that timely completion of these tasks, in collaboration with other groups participating in the analysis of project data is critical to ensure the genetics community obtains maximum benefit from the project. PUBLIC HEALTH RELEVANCE: Reconstructing the genome sequence of many individuals will allow the 1000 Genome Project to deliver catalogs of common genetic variants and the relationships between these variants in the population. These catalogs are an essential component of genetic association studies focused on complex diseases such as diabetes, asthma, cancer and aging associated disorders. In this application, we propose to help design a data collection strategy for the project, to monitor the quality of the primary sequence data, and to analyze the primary sequence data to deliver a processed dataset that is useful to the genetics community at large.