Systematic removal of outliers to reduce heterogeneity in case-control association studies.

ABSTRACT:

Background/aims

In human case-control association studies, population heterogeneity is often present and can lead to increased false-positive results. Various methods have been proposed and are in current use to remedy this situation.

Methods

We assume that heterogeneity is due to a relatively small number of individuals whose allele frequencies differ from those of the remainder of the sample. For this situation, we propose a new method of handling heterogeneity by removing outliers in a controlled manner. In a coordinate system of the c largest principal components in multidimensional scaling (MDS), we systematically remove one after another of the most extreme outlying individuals and each time recompute the largest association test statistic. The smallest p value obtaine

SUBMITTER: Shen Y 

PROVIDER: S-EPMC2975732 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature