Literature DB >> 18931509

Optimal DNA pooling-based two-stage designs in case-control association studies.

Yihong Zhao1, Shuang Wang.   

Abstract

Study cost remains the major limiting factor for genome-wide association studies due to the necessity of genotyping a large number of SNPs for a large number of subjects. Both DNA pooling strategies and two-stage designs have been proposed to reduce genotyping costs. In this study, we propose a cost-effective, two-stage approach with a DNA pooling strategy. During stage I, all markers are evaluated on a subset of individuals using DNA pooling. The most promising set of markers is then evaluated with individual genotyping for all individuals during stage II. The goal is to determine the optimal parameters (pi(p)(sample ), the proportion of samples used during stage I with DNA pooling; and pi(p)(marker ), the proportion of markers evaluated during stage II with individual genotyping) that minimize the cost of a two-stage DNA pooling design while maintaining a desired overall significance level and achieving a level of power similar to that of a one-stage individual genotyping design. We considered the effects of three factors on optimal two-stage DNA pooling designs. Our results suggest that, under most scenarios considered, the optimal two-stage DNA pooling design may be much more cost-effective than the optimal two-stage individual genotyping design, which use individual genotyping during both stages. Copyright 2008 S. Karger AG, Basel.

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Year:  2008        PMID: 18931509      PMCID: PMC2868915          DOI: 10.1159/000164398

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  29 in total

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4.  Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies.

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9.  Identification of a novel risk locus for progressive supranuclear palsy by a pooled genomewide scan of 500,288 single-nucleotide polymorphisms.

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  8 in total

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2.  Analysis and optimal design for association studies using next-generation sequencing with case-control pools.

Authors:  Wei E Liang; Duncan C Thomas; David V Conti
Journal:  Genet Epidemiol       Date:  2012-09-12       Impact factor: 2.135

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4.  On optimal pooling designs to identify rare variants through massive resequencing.

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5.  Genome-wide association study identifies PERLD1 as asthma candidate gene.

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6.  A joint use of pooling and imputation for genotyping SNPs.

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7.  A pooling-based genome-wide analysis identifies new potential candidate genes for atopy in the European Community Respiratory Health Survey (ECRHS).

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  8 in total

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