Literature DB >> 12386837

Upward bias in estimation of genetic effects.

D Siegmund1.   

Abstract

Because of the large number of tests for linkage that are performed in genome scans, the naive estimator of the size of a genetic effect in cases of borderline significance can be inflated and lead to unrealistic expectations for successful replication. As a remedy, this report proposes lower confidence limits that account for the multiple comparisons of the genome scan.

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Year:  2002        PMID： 12386837      PMCID： PMC385094          DOI： 10.1086/343819

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN： 0002-9297            Impact factor:   11.025


  7 in total

1.  Bias in estimates of quantitative-trait-locus effect in genome scans: demonstration of the phenomenon and a method-of-moments procedure for reducing bias.

Authors:  David B Allison; Jose R Fernandez; Moonseong Heo; Shankuan Zhu; Carol Etzel; T Mark Beasley; Christopher I Amos
Journal:  Am J Hum Genet       Date:  2002-02-08       Impact factor: 11.025

2.  Large upward bias in estimation of locus-specific effects from genomewide scans.

Authors:  H H Göring; J D Terwilliger; J Blangero
Journal:  Am J Hum Genet       Date:  2001-10-09       Impact factor: 11.025

3.  Mapping quantitative trait loci in oligogenic models.

Authors:  H K Tang; D Siegmund
Journal:  Biostatistics       Date:  2001-06       Impact factor: 5.899

4.  Linkage strategies for genetically complex traits. I. Multilocus models.

Authors:  N Risch
Journal:  Am J Hum Genet       Date:  1990-02       Impact factor: 11.025

5.  Multipoint linkage analysis using affected relative pairs and partially informative markers.

Authors:  J Teng; D Siegmund
Journal:  Biometrics       Date:  1998-12       Impact factor: 2.571

6.  Gaussian models for genetic linkage analysis using complete high-resolution maps of identity by descent.

Authors:  E Feingold; P O Brown; D Siegmund
Journal:  Am J Hum Genet       Date:  1993-07       Impact factor: 11.025

7.  The investigation of linkage between a quantitative trait and a marker locus.

Authors:  J K Haseman; R C Elston
Journal:  Behav Genet       Date:  1972-03       Impact factor: 2.805
  7 in total
  9 in total

1.  Quantitative founder-effect analysis of French Canadian families identifies specific loci contributing to metabolic phenotypes of hypertension.

Authors:  P Hamet; E Merlo; O Seda; U Broeckel; J Tremblay; M Kaldunski; D Gaudet; G Bouchard; B Deslauriers; F Gagnon; G Antoniol; Z Pausová; M Labuda; M Jomphe; F Gossard; G Tremblay; R Kirova; P Tonellato; S N Orlov; J Pintos; J Platko; T J Hudson; J D Rioux; T A Kotchen; A W Cowley
Journal:  Am J Hum Genet       Date:  2005-03-30       Impact factor: 11.025

2.  Overcoming the winner's curse: estimating penetrance parameters from case-control data.

Authors:  Sebastian Zollner; Jonathan K Pritchard
Journal:  Am J Hum Genet       Date:  2007-02-16       Impact factor: 11.025

3.  Quantifying and correcting for the winner's curse in quantitative-trait association studies.

Authors:  Rui Xiao; Michael Boehnke
Journal:  Genet Epidemiol       Date:  2011-01-31       Impact factor: 2.135

4.  Bias-reduced estimators and confidence intervals for odds ratios in genome-wide association studies.

Authors:  Hua Zhong; Ross L Prentice
Journal:  Biostatistics       Date:  2008-02-28       Impact factor: 5.899

5.  Flexible design for following up positive findings.

Authors:  Kai Yu; Nilanjan Chatterjee; William Wheeler; Qizhai Li; Sophia Wang; Nathaniel Rothman; Sholom Wacholder
Journal:  Am J Hum Genet       Date:  2007-08-03       Impact factor: 11.025

6.  Estimating odds ratios in genome scans: an approximate conditional likelihood approach.

Authors:  Arpita Ghosh; Fei Zou; Fred A Wright
Journal:  Am J Hum Genet       Date:  2008-04-24       Impact factor: 11.025

7.  Quantifying and correcting for the winner's curse in genetic association studies.

Authors:  Rui Xiao; Michael Boehnke
Journal:  Genet Epidemiol       Date:  2009-07       Impact factor: 2.135

8.  Multiple loci contribute to genome-wide recombination levels in male mice.

Authors:  Brenda Murdoch; Nichole Owen; Sofia Shirley; Sara Crumb; Karl W Broman; Terry Hassold
Journal:  Mamm Genome       Date:  2010-11-27       Impact factor: 2.957

9.  A Germline Variant on Chromosome 4q31.1 Associates with Susceptibility to Developing Colon Cancer Metastasis.

Authors:  Sanford D Markowitz; Nora L Nock; Stephanie L Schmit; Zsofia K Stadler; Vijai Joseph; Lu Zhang; Joseph E Willis; Peter Scacheri; Martina Veigl; Mark D Adams; Leon Raskin; John F Sullivan; Kelly Stratton; Jinru Shia; Nathan Ellis; Hedy S Rennert; Christopher Manschreck; Li Li; Kenneth Offit; Robert C Elston; Gadi Rennert; Stephen B Gruber
Journal:  PLoS One       Date:  2016-01-11       Impact factor: 3.240
  9 in total

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