Literature DB >> 15700279

Streamlined analysis of pooled genotype data in SNP-based association studies.

Valentina Moskvina1, Nadine Norton, Nigel Williams, Peter Holmans, Michael Owen, Michael O'donovan.   

Abstract

Several groups have developed methods for estimating allele frequencies in DNA pools as a fast and cheap way for detecting allelic association between genetic markers and disease. To obtain accurate estimates of allele frequencies, a correction factor k for the degree to which measurement of allele-specific products is biased is generally applied. Factor k is usually obtained as the ratio of the two allele-specific signals in samples from heterozygous individuals, a step that can significantly impair throughput and increase cost. We have systematically investigated the properties of k through the use of empirical and simulated data. We show that for the dye terminator primer extension genotyping method we have applied, the correction factor k is substantially influenced by the dye terminators incorporated, but also by the terminal 3' base of the extension primer. We also show that the variation in k is large enough to result in unacceptable error rates if association studies are conducted without regard to k. We show that the impact of ignoring k can be neutralized by applying a correction factor k(max) that can be easily derived, but this at the potential cost of an increase in type I error. Finally, based upon observed distributions for k we derive a method allowing the estimation of the probability pooled data reflects significant differences in the allele frequencies between the subjects comprising the pools. By controlling the error rates in the absence of knowledge of the appropriate SNP-specific correction factors, each approach enhances the performance of DNA pooling, while considerably streamlining the method by reducing time and cost. (c) 2005 Wiley-Liss, Inc.

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Substances:

Year:  2005        PMID: 15700279     DOI: 10.1002/gepi.20062

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  12 in total

1.  Identification of the genetic basis for complex disorders by use of pooling-based genomewide single-nucleotide-polymorphism association studies.

Authors:  John V Pearson; Matthew J Huentelman; Rebecca F Halperin; Waibhav D Tembe; Stacey Melquist; Nils Homer; Marcel Brun; Szabolcs Szelinger; Keith D Coon; Victoria L Zismann; Jennifer A Webster; Thomas Beach; Sigrid B Sando; Jan O Aasly; Reinhard Heun; Frank Jessen; Heike Kolsch; Magdalini Tsolaki; Makrina Daniilidou; Eric M Reiman; Andreas Papassotiropoulos; Michael L Hutton; Dietrich A Stephan; David W Craig
Journal:  Am J Hum Genet       Date:  2006-12-06       Impact factor: 11.025

Review 2.  A generic research paradigm for identification and validation of early molecular diagnostics and new therapeutics in common disorders.

Authors:  Keith D Coon; Travis L Dunckley; Dietrich A Stephan
Journal:  Mol Diagn Ther       Date:  2007       Impact factor: 4.074

3.  Genome-wide pooling approach identifies SPATA5 as a new susceptibility locus for alopecia areata.

Authors:  Lina M Forstbauer; Felix F Brockschmidt; Valentina Moskvina; Christine Herold; Silke Redler; Alexandra Herzog; Axel M Hillmer; Christian Meesters; Stefanie Heilmann; Florian Albert; Margrieta Alblas; Sandra Hanneken; Sibylle Eigelshoven; Kathrin A Giehl; Dagny Jagielska; Ulrike Blume-Peytavi; Natalie Garcia Bartels; Jennifer Kuhn; Hans Christian Hennies; Matthias Goebeler; Andreas Jung; Wiebke K Peitsch; Anne-Katrin Kortüm; Ingrid Moll; Roland Kruse; Gerhard Lutz; Hans Wolff; Bettina Blaumeiser; Markus Böhm; George Kirov; Tim Becker; Markus M Nöthen; Regina C Betz
Journal:  Eur J Hum Genet       Date:  2011-10-26       Impact factor: 4.246

4.  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

5.  A new analysis tool for individual-level allele frequency for genomic studies.

Authors:  Hsin-Chou Yang; Hsin-Chi Lin; Mei-Chu Huang; Ling-Hui Li; Wen-Harn Pan; Jer-Yuarn Wu; Yuan-Tsong Chen
Journal:  BMC Genomics       Date:  2010-07-05       Impact factor: 3.969

6.  PPC: an algorithm for accurate estimation of SNP allele frequencies in small equimolar pools of DNA using data from high density microarrays.

Authors:  Jesper Brohede; Rob Dunne; James D McKay; Garry N Hannan
Journal:  Nucleic Acids Res       Date:  2005-09-30       Impact factor: 16.971

7.  Identification of disease causing loci using an array-based genotyping approach on pooled DNA.

Authors:  David W Craig; Matthew J Huentelman; Diane Hu-Lince; Victoria L Zismann; Michael C Kruer; Anne M Lee; Erik G Puffenberger; John M Pearson; Dietrich A Stephan
Journal:  BMC Genomics       Date:  2005-09-30       Impact factor: 3.969

8.  Analysis of pooled DNA samples on high density arrays without prior knowledge of differential hybridization rates.

Authors:  Stuart Macgregor; Peter M Visscher; Grant Montgomery
Journal:  Nucleic Acids Res       Date:  2006-04-20       Impact factor: 16.971

9.  A genome-wide study of preferential amplification/hybridization in microarray-based pooled DNA experiments.

Authors:  H-C Yang; Y-J Liang; M-C Huang; L-H Li; C-H Lin; J-Y Wu; Y-T Chen; C S J Fann
Journal:  Nucleic Acids Res       Date:  2006-08-23       Impact factor: 16.971

10.  Pooled DNA genotyping on Affymetrix SNP genotyping arrays.

Authors:  George Kirov; Ivan Nikolov; Lyudmila Georgieva; Valentina Moskvina; Michael J Owen; Michael C O'Donovan
Journal:  BMC Genomics       Date:  2006-02-15       Impact factor: 3.969

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