Cited by 421Genetic Mapping and Diversity in Plants and AnimalsGenetic Associations and EpidemiologyGenetic and phenotypic traits in livestock

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A simple correction for multiple comparisons in interval mapping genome scans

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Cheverud, James M·2001·Heredity

DOI 10.1046/j.1365-2540.2001.00901.x

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Abstract

Several approaches have been proposed to correct point-wise significance thresholds used in interval-mapping genome scans. A method for significance threshold correction based on the Bonferroni test is presented. This test involves calculating the effective number of independent comparisons performed in a genome scan from the variance of the eigenvalues of the observed marker correlation matrix. The more highly correlated the markers, the higher the variance of the eigenvalues and the lower the number of independent tests performed on a chromosome. This approach was evaluated by mapping 1000 normally distributed phenotypes along chromosomes of varying length and marker density in a population size of 500. Experiment-wise significance thresholds obtained from the simulation are compared to those calculated using the Bonferroni criterion and the newly developed measure of the effective number of independent tests in a genome scan. The Bonferroni calculation produced significance thresholds very similar to those obtained by simulation. The threshold levels for both Bonferroni and simulation analysis depended strongly on the marker density and size of chromosomes. There was a slight bias of about 1% in the thresholds obtained at the 5% and 10% point-wise significance levels. The method introduced here provides a relatively simple correction for multiple comparisons that can be easily calculated using standard statistics packages.

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Genetics and Analysis of Quantitative Traits
(2002) · Journal of Animal Breeding and Genetics · doi:10.1046/j.1439-0388.2002.00356.x · Cited by 6,176
Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.
Lander, E. S., & Botstein, D. (1989) · Genetics · doi:10.1093/genetics/121.1.185 · Cited by 5,236
Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results
Lander, E. S., & Kruglyak, L. (1995) · Nature Genetics · doi:10.1038/ng1195-241 · Cited by 5,236
Empirical threshold values for quantitative trait mapping.
Churchill, G. A., & Doerge, R. W. (1994) · Genetics · doi:10.1093/genetics/138.3.963 · Cited by 4,935
Precision mapping of quantitative trait loci.
Zeng, Z. B. (1994) · Genetics · doi:10.1093/genetics/136.4.1457 · Cited by 3,182
Genetic Data Analysis II.
Weir, B. S. (1997) · Biometrics · doi:10.2307/2533134 · Cited by 2,263
A simple regression method for mapping quantitative trait loci in line crosses using flanking markers
Haley, C. S., & Knott, S. A. (1992) · Heredity · doi:10.1038/hdy.1992.131 · Cited by 1,991
Genetic dissection of complex traits
Witte, J., Elston, R., & Schork, N. (1996) · Nature Genetics · doi:10.1038/ng0496-355 · Cited by 1,883
Genetic Data Analysis II. By Bruce S. Weir, Sunderland, Massachusetts. Sinauer Associates, Inc.445 pages. ISBN 0-87893-902-4.
Hill, W. G. (1996) · Genetics Research · doi:10.1017/s0016672300034121 · Cited by 921
Multiple trait analysis of genetic mapping for quantitative trait loci.
Jiang, C., & Zeng, Z. (1995) · Genetics · doi:10.1093/genetics/140.3.1111 · Cited by 831

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Authors: Cheverud, J. M.
Affiliations: Washington University in St. Louis (US)
Corresponding author: Cheverud, James M
ORCID: Cheverud, James M
Venue: Heredity
Publisher: Springer Science and Business Media LLC
Published: 2001
Volume: 87
Issue: 1
Pages: 52-58
ISSN: 0018-067X (ISSN-L)
DOI: 10.1046/j.1365-2540.2001.00901.x
OpenAlex: W2054881132
Cited by: 421
References: 21
Citations by year: 2026: 8 · 2025: 16 · 2024: 13 · 2023: 10 · 2022: 21 · 2021: 21 · 2020: 18 · 2019: 9 · 2018: 17 · 2017: 10 · 2016: 30 · 2015: 21 · 2014: 14 · 2013: 24 · 2012: 25
FWCI: 3.43
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Heredity (publishedVersion)
PubMed (publishedVersion)
Funders: National Science Foundation (9726433)
National Institutes of Health (5r01dk052514-06)
National Institute of Diabetes and Digestive and Kidney Diseases (DK52514)
Division of Environmental Biology
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
Keywords: multiple testing correction, interval mapping, genome scan, Bonferroni correction, significance threshold, marker density, chromosome length, QTL mapping
MeSH terms: Analysis of Variance, Biometry, Chromosome Mapping, Computer Simulation, Genetic Markers, Genotype, Genetic Linkage, Models, Genetic, Statistics as Topic, Models, Statistical, Quantitative Trait, Heritable

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A simple correction for multiple comparisons in interval mapping genome scans

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