Efficient identification of context dependent subgroups of risk from genome-wide association studies.

ABSTRACT: We have developed a modified Patient Rule-Induction Method (PRIM) as an alternative strategy for analyzing representative samples of non-experimental human data to estimate and test the role of genomic variations as predictors of disease risk in etiologically heterogeneous sub-samples. A computational limit of the proposed strategy is encountered when the number of genomic variations (predictor variables) under study is large (>500) because permutations are used to generate a null distribution to test the significance of a term (defined by values of particular variables) that characterizes a sub-sample of individuals through the peeling and pasting processes. As an alternative, in this paper we introduce a theoretical strategy that facilitates the quick calculation of Type I and Type II er

SUBMITTER: Dyson G 

PROVIDER: S-EPMC4171947 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature