Literature DB >> 2035526

A note on multiple testing procedures in linkage analysis.

N Risch1.   

Abstract

Controversy over the impact of multiple testing procedures in linkage analysis is reexamined in this report. Despite some recent claims to the contrary, it is shown that testing multiple markers decreases the posterior false-positive rate among significant tests, rather than increasing it; this is true whether the trait of interest is simply monogenic or complex, or even if the genetic model is misspecified. However, if the true mode of inheritance is complex, or if the genetic model is misspecified, the power to obtain a significant result when linkage is present may be reduced, while the significance level is not, leading to an inflation of the posterior false-positive rate. Furthermore, the posterior false-positive rate increases with decreasing sample size and may be unacceptably high for very small samples. By contrast, testing multiple genetic models, by varying either mode-of-inheritance parameters or diagnostic categories, does lead to an inflation of the posterior false-positive rate. A conservative correction for this case is to subtract log10t from the obtained maximum lod score, where t different genetic and/or diagnostic models have been tested.

Mesh:

Year:  1991        PMID: 2035526      PMCID: PMC1683115     

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


  7 in total

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Authors:  R C Elston; K Lange
Journal:  Ann Hum Genet       Date:  1975-01       Impact factor: 1.670

2.  Sequential tests for the detection of linkage.

Authors:  N E MORTON
Journal:  Am J Hum Genet       Date:  1955-09       Impact factor: 11.025

Review 3.  The mapping of human chromosomes.

Authors:  J H Renwick
Journal:  Annu Rev Genet       Date:  1971       Impact factor: 16.830

4.  Caution in locating the gene(s) for affective disorder.

Authors:  J H Edwards; D C Watt
Journal:  Psychol Med       Date:  1989-05       Impact factor: 7.723

Review 5.  Bipolar affective disorders linked to DNA markers on chromosome 11.

Authors:  J A Egeland; D S Gerhard; D L Pauls; J N Sussex; K K Kidd; C R Allen; A M Hostetter; D E Housman
Journal:  Nature       Date:  1987 Feb 26-Mar 4       Impact factor: 49.962

6.  Variability of human linkage data.

Authors:  D C Rao; B J Keats; N E Morton; S Yee; R Lew
Journal:  Am J Hum Genet       Date:  1978-09       Impact factor: 11.025

7.  Interpretation of LOD scores with a set of marker loci.

Authors:  E A Thompson
Journal:  Genet Epidemiol       Date:  1984       Impact factor: 2.135

  7 in total
  21 in total

1.  A confidence-set approach for finding tightly linked genomic regions.

Authors:  S Lin; J A Rogers; J C Hsu
Journal:  Am J Hum Genet       Date:  2001-04-13       Impact factor: 11.025

2.  Controlling the proportion of false positives in multiple dependent tests.

Authors:  R L Fernando; D Nettleton; B R Southey; J C M Dekkers; M F Rothschild; M Soller
Journal:  Genetics       Date:  2004-01       Impact factor: 4.562

Review 3.  Linkage analysis in the next-generation sequencing era.

Authors:  Joan E Bailey-Wilson; Alexander F Wilson
Journal:  Hum Hered       Date:  2011-12-23       Impact factor: 0.444

4.  Generalized linear mixed models for mapping multiple quantitative trait loci.

Authors:  X Che; S Xu
Journal:  Heredity (Edinb)       Date:  2012-03-14       Impact factor: 3.821

5.  Genome scan for human obesity and linkage to markers in 20q13.

Authors:  J H Lee; D R Reed; W D Li; W Xu; E J Joo; R L Kilker; E Nanthakumar; M North; H Sakul; C Bell; R A Price
Journal:  Am J Hum Genet       Date:  1999-01       Impact factor: 11.025

6.  Significance levels in complex inheritance.

Authors:  N E Morton
Journal:  Am J Hum Genet       Date:  1998-03       Impact factor: 11.025

7.  Magnitude of type I error when single-locus linkage analysis is maximized over models: a simulation study.

Authors:  S E Hodge; P C Abreu; D A Greenberg
Journal:  Am J Hum Genet       Date:  1997-01       Impact factor: 11.025

8.  A novel generalized ridge regression method for quantitative genetics.

Authors:  Xia Shen; Moudud Alam; Freddy Fikse; Lars Rönnegård
Journal:  Genetics       Date:  2013-01-18       Impact factor: 4.562

9.  Mapping of an insulin-dependent diabetes locus, Idd9, in NOD mice to chromosome 4.

Authors:  N R Rodrigues; R J Cornall; P Chandler; E Simpson; L S Wicker; L B Peterson; J A Todd
Journal:  Mamm Genome       Date:  1994-03       Impact factor: 2.957

10.  A genome-wide linkage scan identifies multiple chromosomal regions influencing serum lipid levels in the population on the Samoan islands.

Authors:  Karolina Aberg; Feng Dai; Guangyun Sun; Ember Keighley; Subba Rao Indugula; Linda Bausserman; Satupaitea Viali; John Tuitele; Ranjan Deka; Daniel E Weeks; Stephen T McGarvey
Journal:  J Lipid Res       Date:  2008-07-01       Impact factor: 5.922

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