Adaptive Combination of P-values (ADA) method for Association Testing of Clustered Rare Causal Variants


##########################################################################################
# This program was based on Cheung et al.'s code. Thank them for sharing their R code.
# Please cite:
# Lin W-Y (2014). Association Testing of Clustered Rare Causal Variants in Case-Control Studies. PLoS ONE, 9: e94337. [PMID: 24736372].
# and also the paper by Cheung et al. (2012) (listed below). Thank you.
# Any question, please contact: Wan-Yu Lin, linwy@ntu.edu.tw, Institute of Epidemiology and Preventive Medicine, National Taiwan University

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# Sigma-P Method for Rare Variant Analysis.
# Developer: Yee Him Cheung, Columbia University
# Email: patrick@ee.columbia.edu
# Copyright 2012
#
# Reference:
# Y.H. Cheung, G. Wang, S.M. Leal, S. Wang, "A Fast and Noise-Resilient
# Approach to Detect Rare-Variant Associations with Deep Sequencing Data
# for Complex Disorders", Genetic Epidemiology, Sep. 2012.
#########################################################################


The R code to implement the CLUSTER method       Example file: CLUSTERfile       Example file: Mapfile

In R, the code to implement this function is:


source("CLUSTER.r")
CLUSTERTest('CLUSTERfile.txt', 0.05, 1000, 1, 'additive', TRUE, POS = read.table('Map.txt',header=F)[,1], max_d = 20000)        # wait for ~2 seconds


where 'CLUSTERfile.txt' is the data file, in which the first column is the disease status (1: case; 0: control), and column 2 to the last column are the numbers of minor alleles.

The following input elements of this function are:
mafThr = 0.05,           (Exclude SNPs with combined MAF > 0.05)
num_perm = 1000,    (the number of permutations)
midp = TRUE,             (mid P-values according to the Fisher's exact test)
mode = 'additive',      (mode of inheritance = "additive")
twoSided = TRUE        (two-sided test)
POS = read.table('Map.txt',header=F)[,1]        (the map file coding the physical positions of the variants)
max_d = 20000          (a user-specified maximum distance of interest, default = 20 kb)

Output: The output is the P-value of the CLUSTER test.  [Lin W-Y (2014). Association Testing of Clustered Rare Causal Variants in Case-Control Studies. PLoS ONE, 9: e94337. [PMID: 24736372].]



Thanks for your interest.


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