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Published on: June 23, 2012
Estimates of array and pool-construction variance for planning efficient DNA-pooling genome wide association studies
Madalene A Earp1, Maziar Rahmani, Kevin Chew
1Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, BC, Canada.
BMC Medical Genomics
|November 30, 2011
Summary
Pooling DNA for genome-wide association studies (GWAS) significantly reduces costs. This study quantizes variance in allele frequency estimation from DNA pools, offering tools to optimize power for cost-effective GWAS.
Area of Science:
- Genetics
- Bioinformatics
- Statistical genomics
Background:
- Genome-wide association studies (GWAS) traditionally require substantial financial investment for genotyping.
- Pool-based GWAS offers a cost-effective alternative by genotyping DNA pools instead of individuals.
- Accurate SNP allele frequency estimation from DNA pools is crucial for the power of pool-based GWAS.
Purpose of the Study:
- To quantify the sources of variance in SNP allele frequency estimation from DNA pools.
- To provide guidance on planning and conducting efficient, well-powered pool-based GWAS.
- To develop a tool for assessing the impact of pooling on study power.
Main Methods:
- Analyzed variance in allele frequency estimation on SNP arrays within and between DNA pools.
- Quantified array variance [var(e(array))] and pool-construction variance [var(e(construction))].
- Utilized data from 27 DNA pools (74-446 samples each) genotyped on 128 Illumina beadarrays.
Main Results:
- Estimates of var(e(array)) were consistent across Illumina array types (3-4 × 10-4 for normalized data).
- Var(e(construction)) contributed 20-40% of the total pooling variance in normalized data.
- Pool-construction variance was found to be more important than previously considered.
Conclusions:
- Pool-construction variance plays a significant role in overall pooling variance, contrary to some prior assumptions.
- A new online tool, PoolingPlanner, calculates effective sample size (ESS) to assess power loss in pool-based GWAS.
- The tool aids researchers in making informed decisions about the feasibility and design of pool-based GWAS.
Related Concept Videos
01:11Genome-wide Association Studies-GWAS
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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GWAS does not require the identification of the target gene involved in...
02:34DNA Microarrays
Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...