Literature DB >> 17264871

Most pooling variation in array-based DNA pooling is attributable to array error rather than pool construction error.

Stuart Macgregor1.   

Abstract

Genome-wide association (GWA) approaches are important in complex disease gene mapping studies but are often prohibitively expensive. Array-based DNA pooling has been shown to offer substantial cost savings compared with individual genotyping. This reduced cost potentially brings well-powered GWA studies well within the reach of most laboratories. The main factor, which affects the efficiency of pooling compared with individual genotyping is the magnitude of the pooling error variance. By examining variation between and within pools it is shown that most of the error associated with pooling is attributable to array variation not pooling construction variation (assuming the pools are not small and the pools are accurately constructed). With Affymetrix HindIII 50K arrays used here the array-specific variance is seven times the pooling construction variance. This has important implications for optimal study design for array-based pooling. Given carefully constructed pools, resources should be allocated to increasing the number of arrays per sample rather than to constructing multiple pools.

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Year:  2007        PMID: 17264871     DOI: 10.1038/sj.ejhg.5201768

Source DB:  PubMed          Journal:  Eur J Hum Genet        ISSN: 1018-4813            Impact factor:   4.246


  31 in total

1.  High-throughput discovery of rare insertions and deletions in large cohorts.

Authors:  Francesco L M Vallania; Todd E Druley; Enrique Ramos; Jue Wang; Ingrid Borecki; Michael Province; Robi D Mitra
Journal:  Genome Res       Date:  2010-11-01       Impact factor: 9.043

2.  Multimarker analysis and imputation of multiple platform pooling-based genome-wide association studies.

Authors:  Nils Homer; Waibhav D Tembe; Szabolcs Szelinger; Margot Redman; Dietrich A Stephan; John V Pearson; Stanley F Nelson; David Craig
Journal:  Bioinformatics       Date:  2008-07-10       Impact factor: 6.937

3.  A comparison of association statistics between pooled and individual genotypes.

Authors:  Jo Knight; Scott F Saccone; Zhehao Zhang; Dennis G Ballinger; John P Rice
Journal:  Hum Hered       Date:  2009-01-27       Impact factor: 0.444

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

Authors:  Yihong Zhao; Shuang Wang
Journal:  Hum Hered       Date:  2008-10-17       Impact factor: 0.444

5.  Rapid inexpensive genome-wide association using pooled whole blood.

Authors:  Jamie E Craig; Alex W Hewitt; Amy E McMellon; Anjali K Henders; Lingjun Ma; Leanne Wallace; Shiwani Sharma; Kathryn P Burdon; Peter M Visscher; Grant W Montgomery; Stuart MacGregor
Journal:  Genome Res       Date:  2009-10-03       Impact factor: 9.043

6.  A genome-wide association study of essential hypertension in an Australian population using a DNA pooling approach.

Authors:  Javed Y Fowdar; Rebecca Grealy; Yi Lu; Lyn R Griffiths
Journal:  Mol Genet Genomics       Date:  2016-11-19       Impact factor: 3.291

7.  Methodological Issues in Multistage Genome-wide Association Studies.

Authors:  Duncan C Thomas; Graham Casey; David V Conti; Robert W Haile; Juan Pablo Lewinger; Daniel O Stram
Journal:  Stat Sci       Date:  2009-11-01       Impact factor: 2.901

8.  Pooled versus individual genotyping in a breast cancer genome-wide association study.

Authors:  Ying Huang; David A Hinds; Lihong Qi; Ross L Prentice
Journal:  Genet Epidemiol       Date:  2010-09       Impact factor: 2.135

9.  Identification of rare alleles and their carriers using compressed se(que)nsing.

Authors:  Noam Shental; Amnon Amir; Or Zuk
Journal:  Nucleic Acids Res       Date:  2010-08-10       Impact factor: 16.971

10.  Validation of pooled genotyping on the Affymetrix 500 k and SNP6.0 genotyping platforms using the polynomial-based probe-specific correction.

Authors:  Ramani Anantharaman; Fook Tim Chew
Journal:  BMC Genet       Date:  2009-12-14       Impact factor: 2.797

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