A simple correction for multiple comparisons in interval mapping genome scans

Cheverud, James M.
July 2001
Heredity;Jul2001, Vol. 87 Issue 1, p52
Academic Journal
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.


Related Articles

  • Linking genotype to phenotype: the International Rice Information System (IRIS). K.L. McNally; R.M. Bruskiewich; R. Sackville Hamilton; A.B. Cosico; C.G. McLaren; W. Eusebio; A.M. Portugal; L.M. Ramos; M.T. Reyes; M.A.B. Sallan; V.J.M. Ulat; X. Wang // Bioinformatics;Jan2009 Supplement, Vol. 19, p63 

    The International Rice Information System (IRIS, http://www.iris.irri.org) is the rice implementation of the International Crop Information System (ICIS, http://www.icis.cgiar.org), a database system for the management and integration of global information on genetic resources and germplasm...

  • Modeling Evolution of Regulatory Networks in Artificial Organisms. Sánchez-Dehesa, Yolanda; Beslon, Guillaume; Peña, José-María // AIP Conference Proceedings;9/18/2007, Vol. 940 Issue 1, p87 

    Regulatory networks are not randomly connected. They are modular, scale-free networks and some motifs distribution is clearly different from random distribution. However, the evolutionary causes and consequences of this specific connectivity are mainly unknown. In this paper we propose Raevol,...

  • Selective Phenotyping for Increased Efficiency in Genetic Mapping Studies. Chunfang Jin; Hong Lan; Attie, Alan D.; Churchill, Gary A.; Bulutuglo, Dursun; Yandell, Brian S. // Genetics;Dec2004, Vol. 168 Issue 4, p2285 

    The power of a genetic mapping study depends on the heritability of the trait, the number of individuals included in the analysis, and the genetic dissimilarity among them. In experiments that involve microarrays or other complex physiological assays, phenotyping can be expensive and...

  • Confidence set of putative quantitative trait loci in whole genome scans with application to the Genetic Analysis Workshop 17 simulated data. Papachristou, Charalampos // BMC Proceedings;2011 Supplement 9, Vol. 5 Issue Suppl 9, p1 

    As genetic maps become more highly dense, the ability to sufficiently localize putative disease loci becomes an achievable goal. This has prompted an increased interest in methods for constructing confidence intervals for the location of variants that contribute to a trait. Such intervals are...

  • A review of statistical methods for expression quantitative trait loci mapping. Kendziorski, Christina; Ping Wang // Mammalian Genome;Jun2006, Vol. 17 Issue 6, p509 

    With high-throughput technologies now widely available, investigators can easily measure thousands of phenotypes for quantitative trait loci (QTL) mapping. Microarray measurements are particularly amenable to QTL mapping, as evidenced by a number of recent studies demonstrating utility across a...

  • Genetic dissection of rice grain shape using a recombinant inbred line population derived from two contrasting parents and fine mapping a pleiotropic quantitative trait locus qGL7. Xufeng Bai; Lijun Luo; Wenhao Yan; Rao Kovi, Mallikarjuna; Wei Zhan; Xing, Yongzhong // BMC Genetics;2010, Vol. 11, p16 

    Background: The three-dimensional shape of grain, measured as grain length, width, and thickness (GL, GW, and GT), is one of the most important components of grain appearance in rice. Determining the genetic basis of variations in grain shape could facilitate efficient improvements in grain...

  • SSR and EST-SSR-based genetic linkage map of cassava ( Manihot esculenta Crantz). Sraphet, Supajit; Boonchanawiwat, Athipong; Thanyasiriwat, Thanwanit; Boonseng, Opas; Tabata, Satoshi; Sasamoto, Shigemi; Shirasawa, Kenta; Isobe, Sachiko; Lightfoot, David; Tangphatsornruang, Sithichoke; Triwitayakorn, Kanokporn // Theoretical & Applied Genetics;Apr2011, Vol. 122 Issue 6, p1161 

    Simple sequence repeat (SSR) markers provide a powerful tool for genetic linkage map construction that can be applied for identification of quantitative trait loci (QTL). In this study, a total of 640 new SSR markers were developed from an enriched genomic DNA library of the cassava variety...

  • Allele-Specific Gene Expression Is Widespread Across the Genome and Biological Processes. Palacios, Ricardo; Gazave, Elodie; Goñi, Joaquín; Piedrafita, Gabriel; Fernando, Olga; Navarro, Arcadi; Villoslada, Pablo // PLoS ONE;2009, Vol. 4 Issue 1, p1 

    Allelic specific gene expression (ASGE) appears to be an important factor in human phenotypic variability and as a consequence, for the development of complex traits and diseases. In order to study ASGE across the human genome, we have performed a study in which genotyping was coupled with an...

  • Identification of functional CNV region networks using a CNV-gene mapping algorithm in a genome-wide scale. Park, Chihyun; Ahn, Jaegyoon; Yoon, Youngmi; Park, Sanghyun // Bioinformatics;8/1/2012, Vol. 28 Issue 15, p2045 

    Motivation: Identifying functional relation of copy number variation regions (CNVRs) and gene is an essential process in understanding the impact of genotypic variations on phenotype. There have been many related works, but only a few attempts were made to normal populations.Results: To analyze...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics