Multiple testing in transformed space (MultiTrans)
Multiple hypothesis testing is an essential step in GWAS analysis. Although the use of 5 × 10-8 has predominated human GWAS, the correct per-marker threshold differs as a function of species, marker densities, genetic relatedness, and trait heritability. However, no previous multiple testing correction methods can comprehensively account for these factors; therefore, these methods are not applicable for linear mixed models. MultiTrans is an efficient and accurate multiple testing correction approach for linear mixed models. Our method performs a unique transformation of genotype data to account for genetic relatedness and heritability under linear mixed models, as well as to efficiently utilize the multivariate normal distribution.
The R implementation of MultiTrans is available. Please refer to the Documentation link for further information. If you have you any further question, please contact Jong Wha J Joo. This is the joint work with Farhad hormozdiari, Buhm Han, and Eleazar Eskin.
This web-site is based upon work supported by the National Science Foundation under Grant No. 0513599 and 0729049. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.