Copyright © 2004 The American Society of Human Genetics. All rights reserved.
The American Journal of Human Genetics, Volume 74, Issue 4, 765-769, 1 April 2004
doi:10.1086/383251
Report
Address for correspondence and reprints: Dr. Dale R. Nyholt, Queensland Institute of Medical Research, Post Office Royal Brisbane Hospital, Brisbane QLD 4029, AustraliaAbstract
In this report, we describe a simple correction for multiple testing of single-nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with each other, on the basis of the spectral decomposition (SpD) of matrices of pairwise LD between SNPs. This method provides a useful alternative to more computationally intensive permutation tests. A user-friendly interface (SNPSpD) for performing this correction is available online (http://genepi.qimr.edu.au/general/daleN/SNPSpD/). Additionally, output from SNPSpD includes eigenvalues, principal-component coefficients, and factor “loadings” after varimax rotation, enabling the selection of a subset of SNPs that optimize the information in a genomic region.
| So Many Correlated Tests, So Little Time! Rapid Adjustment of P Values for Multiple Correlated Tests The American Journal of Human Genetics, Volume 81, Issue 6, 1 December 2007, Pages 1158-1168 Karen N. Conneely and Michael Boehnke Abstract Contemporary genetic association studies may test hundreds of thousands of genetic variants for association, often with multiple binary and continuous traits or under more than one model of inheritance. Many of these association tests may be correlated with one another because of linkage disequilibrium between nearby markers and correlation between traits and models. Permutation tests and simulation-based methods are often employed to adjust groups of correlated tests for multiple testing, since conventional methods such as Bonferroni correction are overly conservative when tests are correlated. We present here a method of computing P values adjusted for correlated tests (PACT) that attains the accuracy of permutation or simulation-based tests in much less computation time, and we show that our method applies to many common association tests that are based on multiple traits, markers, and genetic models. Simulation demonstrates that PACT attains the power of permutation testing and provides a valid adjustment for hundreds of correlated association tests. In data analyzed as part of the Finland–United States Investigation of NIDDM Genetics (FUSION) study, we observe a near one-to-one relationship (r2>.999) between PACT and the corresponding permutation-based P values, achieving the same precision as permutation testing but thousands of times faster. Abstract | | |
| A Discordant-Sibship Test for Disequilibrium and Linkage: No Need for Parental Data The American Journal of Human Genetics, Volume 63, Issue 6, 1 December 1998, Pages 1886-1897 Steve Horvath and Nan M. Laird Abstract Summary:
The sibship disequilibrium test (SDT) is designed to detect both linkage in the presence of association and association in the presence of linkage (linkage disequilibrium). The test does not require parental data but requires discordant sibships with at least one affected and one unaffected sibling. The SDT has many desirable properties: it uses all the siblings in the sibship; it remains valid if there are misclassifications of the affectation status; it does not detect spurious associations due to population stratification; asymptotically it has a χ2 distribution under the null hypothesis; and exact P values can be easily computed for a biallelic marker. We show how to extend the SDT to markers with multiple alleles and how to combine families with parents and data from discordant sibships. We discuss the power of the test by presenting sample-size calculations involving a complex disease model, and we present formulas for the asymptotic relative efficiency (which is approximately the ratio of sample sizes) between SDT and the transmission/disequilibrium test (TDT) for special family structures. For sib pairs, we compare the SDT to a test proposed both by Curtis and, independently, by Spielman and Ewens. We show that, for discordant sib pairs, the SDT has good power for testing linkage disequilibrium relative both to Curtis's tests and to the TDT using trios comprising an affected sib and its parents. With additional sibs, we show that the SDT can be more powerful than the TDT for testing linkage disequilibrium, especially for disease prevalence >.3. Abstract | | |
| Identification of Susceptibility Genes for Cancer in a Genome-wide Scan: Results from the Colon Neoplasia Sibling Study The American Journal of Human Genetics, Volume 82, Issue 3, 3 March 2008, Pages 723-736 Denise Daley, Susan Lewis, Petra Platzer, Melissa MacMillen, Joseph Willis, Robert C. Elston, Sanford D. Markowitz and Georgia L. Wiesner Abstract Colorectal cancer (CRC) is the third most commonly diagnosed cancer in Americans and is the second leading cause of cancer mortality. Only a minority (∼5%) of familial CRC can be explained by known genetic variants. To identify susceptibility genes for familial colorectal neoplasia, the colon neoplasia sibling study conducted a comprehensive, genome-wide linkage scan of 194 kindreds. Clinical information (histopathology, size and number of polyps, and other primary cancers) was used in conjunction with age at onset and family history for classification of the families into five phenotypic subgroups (severe histopathology, oligopolyposis, young, colon/breast, and multiple cancer) prior to analysis. By expanding the traditional affected-sib-pair design to include unaffected and discordant sib pairs, analytical power and robustness to type I error were increased. Sib-pair linkage statistics and Haseman-Elston regression identified 19 linkage peaks, with interesting results for chromosomes 1p31.1, 15q14-q22, 17p13.3, and 21. At marker D1S1665 (1p31.1), there was strong evidence for linkage in the multiple-cancer subgroup (p = 0.00007). For chromosome 15q14-q22, a linkage peak was identified in the full-sample (p = 0.018), oligopolyposis (p = 0.003), and young (p = 0.0009) phenotypes. This region includes the HMPS/CRAC1 locus associated with hereditary mixed polyposis syndrome (HMPS) in families of Ashkenazi descent. We provide compelling evidence linking this region in families of European descent with oligopolyposis and/or young age at onset (≤51) phenotypes. We found linkage to BRCA2 in the colon/breast phenotypic subgroup and identified a second locus in the region of D21S1437 segregating with, but distinct from, BRCA2. Linkage to 17p13.3 at marker D17S1308 in the breast/colon subgroup identified HIC1 as a candidate gene. We demonstrated that using clinical information, unaffected siblings, and family history can increase the analytical power of a linkage study. Abstract | | |