Ranking of genome-wide association scan signals by different measures.

2.50
Hdl Handle:
http://hdl.handle.net/10146/114666
Title:
Ranking of genome-wide association scan signals by different measures.
Authors:
Stromberg, Ulf; Bjork, Jonas; Vineis, Paolo; Broberg, Karin; Zeggini, Eleftheria
Abstract:
BACKGROUND: The P-value approach has been employed to prioritizing genome-wide association (GWA) scan signals, with a genome-wide significance defined by a prior P-value threshold, although this is not ideal. A rationale put forward is that the association signals rather should be expected to give less support for single nucleotide polymorphisms (SNPs) that are rare (with associated low-power tests) than for common SNPs with equivalent P-values, unless investigators believe, a priori, that rare causative variants contribute to the disease and have more pronounced effects. METHODS: Using data from a GWA scan for type 2 diabetes (1924 cases, 2938 controls, 393 453 SNPs), we compared P-values with four alternative signal measures: likelihood ratio (LR), Bayes factor (BF; with a specified prior distribution for true effects), 'frequentist factor' (FF; reflecting the ratio between estimated--post-data-- 'power' and P-value) and probability of pronounced effect size (PrPES). RESULTS: The 19 common SNPs [minor allele frequency (MAF) among the controls >29%] yielding strong P-value signals (P < 5 x 10(-7)) were also top ranked by the other approaches. There was a strong similarity between the P-values, LR and BF signals, in terms of ranking SNPs. In contrast, FF and PrPES signals down-weighted rare SNPs (control MAF <10%) with low P-values. CONCLUSIONS: For prioritization of signals that do not achieve compelling levels of evidence for association, the main driving force behind observed differences between the various association signals appears to be SNP MAF. The statistical power afforded by follow-up samples for establishing replication should be taken into account when tailoring the signal selection strategy.
Citation:
Int. J. Epidemiol. 2009, 38 (5):1364-1373
Journal:
International Journal of Epidemiology
Issue Date:
Oct-2009
URI:
http://hdl.handle.net/10146/114666
DOI:
10.1093/ije/dyp285
PubMed ID:
19734549
Additional Links:
http://ije.oxfordjournals.org/content/38/5/1364.long
Type:
Article
Language:
en
ISSN:
1464-3685
Sponsors:
This work was partly conducted within the EU Network of Excellence ECNIS (http://www.ecnis .org).
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorStromberg, Ulfen
dc.contributor.authorBjork, Jonasen
dc.contributor.authorVineis, Paoloen
dc.contributor.authorBroberg, Karinen
dc.contributor.authorZeggini, Eleftheriaen
dc.date.accessioned2010-11-04T09:50:26Z-
dc.date.available2010-11-04T09:50:26Z-
dc.date.issued2009-10-
dc.identifier.citationInt. J. Epidemiol. 2009, 38 (5):1364-1373en
dc.identifier.issn1464-3685-
dc.identifier.pmid19734549-
dc.identifier.doi10.1093/ije/dyp285-
dc.identifier.urihttp://hdl.handle.net/10146/114666-
dc.description.abstractBACKGROUND: The P-value approach has been employed to prioritizing genome-wide association (GWA) scan signals, with a genome-wide significance defined by a prior P-value threshold, although this is not ideal. A rationale put forward is that the association signals rather should be expected to give less support for single nucleotide polymorphisms (SNPs) that are rare (with associated low-power tests) than for common SNPs with equivalent P-values, unless investigators believe, a priori, that rare causative variants contribute to the disease and have more pronounced effects. METHODS: Using data from a GWA scan for type 2 diabetes (1924 cases, 2938 controls, 393 453 SNPs), we compared P-values with four alternative signal measures: likelihood ratio (LR), Bayes factor (BF; with a specified prior distribution for true effects), 'frequentist factor' (FF; reflecting the ratio between estimated--post-data-- 'power' and P-value) and probability of pronounced effect size (PrPES). RESULTS: The 19 common SNPs [minor allele frequency (MAF) among the controls >29%] yielding strong P-value signals (P < 5 x 10(-7)) were also top ranked by the other approaches. There was a strong similarity between the P-values, LR and BF signals, in terms of ranking SNPs. In contrast, FF and PrPES signals down-weighted rare SNPs (control MAF <10%) with low P-values. CONCLUSIONS: For prioritization of signals that do not achieve compelling levels of evidence for association, the main driving force behind observed differences between the various association signals appears to be SNP MAF. The statistical power afforded by follow-up samples for establishing replication should be taken into account when tailoring the signal selection strategy.en
dc.description.sponsorshipThis work was partly conducted within the EU Network of Excellence ECNIS (http://www.ecnis .org).en
dc.language.isoenen
dc.relation.urlhttp://ije.oxfordjournals.org/content/38/5/1364.longen
dc.subjectDiabetes Mellitusen
dc.subjectGenetic Predisposition to Diseaseen
dc.subjectGenomeen
dc.subjectHumansen
dc.subjectGenome-Wide Association Studyen
dc.subjectepidemiologyen
dc.subject.meshBayes Theorem-
dc.subject.meshDiabetes Mellitus, Type 2-
dc.subject.meshGenetic Predisposition to Disease-
dc.subject.meshGenome, Human-
dc.subject.meshGenome-Wide Association Study-
dc.subject.meshHumans-
dc.subject.meshPolymorphism, Single Nucleotide-
dc.titleRanking of genome-wide association scan signals by different measures.en
dc.typeArticleen
dc.identifier.journalInternational Journal of Epidemiologyen

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