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KBAC with Permutation Testing

Author: James Grover, Golden Helix, Inc.

The Kernel-Based Adaptive Cluster (KBAC) method by Liu and Leal [Liu and Leal 2010] first catalogs the variant data within each of a number of regions into multi-marker genotypes. Since the variants are rare, only a relatively few different multi-marker genotypes will be found in any given region.

A special case/control test based on these counts is then applied. This test is weighted for each multi-marker genotype according to how often that genotype is expected to occur according to the data and according to the null hypothesis that there is no association between that genotype and the case/control status of the sample. Under this adaptive weighting procedure, the genotypes with high sample risks will be given higher weights which can potentially separate causal from non-causal genotypes. This procedure is meant to attain a good balance between classification accuracy and the number of parameters which are estimated.

	KBAC with Permutation Testing.pyc
	Documentation

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Save the script to the following directory:
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Note: The Application Data folder is a hidden folder on Windows operating systems and its location varies between XP and Vista. The easiest way to locate this directory on your computer is to open SVS and go to Tools >Open Folder > UserScripts Folder. If saved to the proper folder, this script will be accessible from the spreadsheet Analysis menu.