Multiple phenotypes in genome-wide genetic mapping studies

Jurg Ott, Jing Wang()

PDF(115 KB)
PDF(115 KB)
Protein Cell ›› 2011, Vol. 2 ›› Issue (7) : 519-522. DOI: 10.1007/s13238-011-1059-5
MINI-REVIEW

Multiple phenotypes in genome-wide genetic mapping studies

  • Jurg Ott, Jing Wang()
Author information +
History +

Abstract

For many psychiatric and other traits, diagnoses are based on a number of different criteria or phenotypes. Rather than carrying out genetic analyses on the final diagnosis, it has been suggested that relevant phenotypes should be analyzed directly. We provide an overview of statistical methods for the joint analysis of multiple phenotypes in case-control association studies.

Keywords

multiple phenotypes / genetic mapping / case-control / statistical method

Cite this article

Download citation ▾
Jurg Ott, Jing Wang. Multiple phenotypes in genome-wide genetic mapping studies. Prot Cell, 2011, 2(7): 519‒522 https://doi.org/10.1007/s13238-011-1059-5

References

[1] Allison, D.B., Thiel, B., St Jean, P., Elston, R.C., Infante, M.C., and Schork, N.J. (1998). Multiple phenotype modeling in gene-mapping studies of quantitative traits: power advantages.Am J Hum Genet 63, 1190-1201 .9758596
[2] Benjamini, Y. (2010). Discovering the false discovery rate. J R Stat Soc, B 72, 405-416 .
[3] Benjamini, Y., Drai, D., Elmer, G., Kafkafi, N., and Golani, I. (2001). Controlling the false discovery rate in behavior genetics research. Behav Brain Res 125, 279-284 .11682119
[4] Bookman, E.B., Taylor, R.E., Adams-Campbell, L., and Kittles, R.A. (2002). DRD4 promoter SNPs and gender effects on Extraversion in African Americans. Mol Psychiatry 7, 786-789 .12192624
[5] Braff, D.L., Freedman, R., Schork, N.J., and Gottesman, I.I. (2007). Deconstructing schizophrenia: an overview of the use of endophenotypes in order to understand a complex disorder. Schizophr Bull 33, 21-32 .17088422
[6] Cheverud, J.M. (2001). A simple correction for multiple comparisons in interval mapping genome scans. Heredity 87, 52-58 .11678987
[7] DeVellis, R.F. (2003). Scale development: theory and applications, 2nd ed.Thousand Oaks, Calif.: Sage Publications, Inc. viii, 171.
[8] Dubay, C., Vincent, M., Samani, N.J., Hilbert, P., Kaiser, M.A., Beressi, J.P., Kotelevtsev, Y., Beckmann, J.S., Soubrier, F., Sassard, J., (1993). Genetic determinants of diastolic and pulse pressure map to different loci in Lyon hypertensive rats. Nat Genet 3, 354-357 .7981757
[9] Hoh, J., and Ott, J. (2000). Scan statistics to scan markers for susceptibility genes. Proc Natl Acad Sci U S A 97, 9615-9617 .10931953
[10] Hoh, J., Wille, A., and Ott, J. (2001). Trimming, weighting, and grouping SNPs in human case-control association studies. Genome Res 11, 2115-2119 .11731502
[11] Holmkvist, J., Banasik, K., Andersen, G., Unoki, H., Jensen, T.S., Pisinger, C., Borch-Johnsen, K., Sandbaek, A., Lauritzen, T., Brunak, S.,(2009). The type 2 diabetes associated minor allele of rs2237895 KCNQ1 associates with reduced insulin release following an oral glucose load. PLoS One 4, e5872.19516902
[12] Klei, L., Luca, D., Devlin, B., and Roeder, K. (2008). Pleiotropy and principal components of heritability combine to increase power for association analysis. Genet Epidemiol 32, 9-19 .17922480
[13] Lander, E., and Kruglyak, L. (1995). Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nat Genet 11, 241-247 .7581446
[14] Manly, B.F.J. (2007). Randomization, bootstrap, and Monte Carlo methods in biology, 3rd ed. Boca Raton, FL: Chapman & Hall/ CRC, 455
[15] Nyholt, D.R. (2004). A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other. Am J Hum Genet 74, 765-769 .14997420
[16] Ott, J. (2004). Association of genetic loci: Replication or not, that is the question. Neurology 63, 955-958 .15452283
[17] Ott, J., and Rabinowitz, D. (1999). A principal-components approach based on heritability for combining phenotype information. Hum Hered 49, 106-111 .10077732
[18] Patterson, N., Price, A.L., and Reich, D. (2006). Population structure and eigenanalysis. PLoS Genet 2, e190.17194218
[19] Pe’er, I., Yelensky, R., Altshuler, D., and Daly, M.J. (2008). Estimation of the multiple testing burden for genomewide association studies of nearly all common variants. Genet Epidemiol 32, 381-385 .18348202
[20] Price, A.L., Patterson, N.J., Plenge, R.M., Weinblatt, M.E., Shadick, N.A., and Reich, D. (2006). Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38, 904-909 .16862161
[21] Zhang, Q., and Ott, J. (2009). Multiple Comparisons/Testing Issues. In: Handbook on Analyzing Human Genetic Data: Computational Approaches and Software. S. Lin, and H. Zhao,Berlin: Springer. 277-287 .
AI Summary AI Mindmap
PDF(115 KB)

Accesses

Citations

Detail

Sections
Recommended

/