DOI: 10.5176/2251-1911_CMCGS13.34
Authors: Ying-Chao Lin, Cathy S.J. Fann, Iebin Lian
Abstract:
High-density genotyping arrays containing millions genetic markers had become an important tool of genome-wide association studies for identifying disease susceptibility genes in common disease genetics research. To cope with the problems of multiple-comparison and over-adjustment, Lin et al. (2012) proposed an efficient maximal segmental score
(MSS) method which uses region-specific empirical pvalues to identify genomic segments harboring the disease gene. In the procedure the original raw data is needed to enable the permutation step for pertaining the p-value of the test statistics. In this work, we adapted the asypmtotic results by Karlin and Dembo (1992) so that the MSS could also be raw-data-free and design-independent.
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