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Article: Impact and quantification of the sources of error in DNA pooling designs

TitleImpact and quantification of the sources of error in DNA pooling designs
Authors
KeywordsDNA pooling
Experimental errors
Genetic association analyses
Issue Date2009
PublisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/AHG
Citation
Annals Of Human Genetics, 2009, v. 73 n. 1, p. 118-124 How to Cite?
AbstractThe analysis of genome wide variation offers the possibility of unravelling the genes involved in the pathogenesis of disease. Genome wide association studies are also particularly useful for identifying and validating targets for therapeutic intervention as well as for detecting markers for drug efficacy and side effects. The cost of such large-scale genetic association studies may be reduced substantially by the analysis of pooled DNA from multiple individuals. However, experimental errors inherent in pooling studies lead to a potential increase in the false positive rate and a loss in power compared to individual genotyping. Here we quantify various sources of experimental error using empirical data from typical pooling experiments and corresponding individual genotyping counts using two statistical methods. We provide analytical formulas for calculating these different errors in the absence of complete information, such as replicate pool formation, and for adjusting for the errors in the statistical analysis. We demonstrate that DNA pooling has the potential of estimating allele frequencies accurately, and adjusting the pooled allele frequency estimates for differential allelic amplification considerably improves accuracy. Estimates of the components of error show that differential allelic amplification is the most important contributor to the error variance in absolute allele frequency estimation, followed by allele frequency measurement and pool formation errors. Our results emphasise the importance of minimising experimental errors and obtaining correct error estimates in genetic association studies. © 2008 The Authors Journal compilation © 2008 Blackwell Publishing Ltd/University College London.
Persistent Identifierhttp://hdl.handle.net/10722/59692
ISSN
2015 Impact Factor: 1.889
2015 SCImago Journal Rankings: 1.191
ISI Accession Number ID
Funding AgencyGrant Number
National Eye InstituteEY-12562
Funding Information:

We would like to thank Ruth March and Neil Gibson for helpful comments. This research was in part supported by a grant from the National Eye Institute EY-12562, recipient Pak Sham.

References

 

DC FieldValueLanguage
dc.contributor.authorJawaid, Aen_HK
dc.contributor.authorSham, Pen_HK
dc.date.accessioned2010-05-31T03:55:29Z-
dc.date.available2010-05-31T03:55:29Z-
dc.date.issued2009en_HK
dc.identifier.citationAnnals Of Human Genetics, 2009, v. 73 n. 1, p. 118-124en_HK
dc.identifier.issn0003-4800en_HK
dc.identifier.urihttp://hdl.handle.net/10722/59692-
dc.description.abstractThe analysis of genome wide variation offers the possibility of unravelling the genes involved in the pathogenesis of disease. Genome wide association studies are also particularly useful for identifying and validating targets for therapeutic intervention as well as for detecting markers for drug efficacy and side effects. The cost of such large-scale genetic association studies may be reduced substantially by the analysis of pooled DNA from multiple individuals. However, experimental errors inherent in pooling studies lead to a potential increase in the false positive rate and a loss in power compared to individual genotyping. Here we quantify various sources of experimental error using empirical data from typical pooling experiments and corresponding individual genotyping counts using two statistical methods. We provide analytical formulas for calculating these different errors in the absence of complete information, such as replicate pool formation, and for adjusting for the errors in the statistical analysis. We demonstrate that DNA pooling has the potential of estimating allele frequencies accurately, and adjusting the pooled allele frequency estimates for differential allelic amplification considerably improves accuracy. Estimates of the components of error show that differential allelic amplification is the most important contributor to the error variance in absolute allele frequency estimation, followed by allele frequency measurement and pool formation errors. Our results emphasise the importance of minimising experimental errors and obtaining correct error estimates in genetic association studies. © 2008 The Authors Journal compilation © 2008 Blackwell Publishing Ltd/University College London.en_HK
dc.languageengen_HK
dc.publisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/AHGen_HK
dc.relation.ispartofAnnals of Human Geneticsen_HK
dc.rightsAnnals of Human Genetics. Copyright © Blackwell Publishing Ltd.en_HK
dc.subjectDNA poolingen_HK
dc.subjectExperimental errorsen_HK
dc.subjectGenetic association analysesen_HK
dc.titleImpact and quantification of the sources of error in DNA pooling designsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0003-4800&volume=73 &issue=1&spage=118&epage=124&date=2009&atitle=Impact+and+Quantification+of+the+Sources+of+Error+in+DNA+Pooling+Designsen_HK
dc.identifier.emailSham, P: pcsham@hku.hken_HK
dc.identifier.authoritySham, P=rp00459en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/j.1469-1809.2008.00486.xen_HK
dc.identifier.pmid18945289-
dc.identifier.scopuseid_2-s2.0-58149301372en_HK
dc.identifier.hkuros158147en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-58149301372&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume73en_HK
dc.identifier.issue1en_HK
dc.identifier.spage118en_HK
dc.identifier.epage124en_HK
dc.identifier.isiWOS:000262149600013-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridJawaid, A=12787441800en_HK
dc.identifier.scopusauthoridSham, P=34573429300en_HK
dc.identifier.citeulike3505370-

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