Description Usage Arguments Details Author(s) References See Also Examples
Diagnostic checking of Wtest probability distribution estimation.
1 2 
data 
a data frame or matrix containing genotypes in the columns. Genotypes should be coded as (0, 1, 2) or (0, 1). 
w.order 
an integer value of 0 or 1. 
n.rep 
a numeric value, the number of bootstrapping times. 
n.sample 
a numeric value, the number of samples to use in bootstrapping. Default is the total number of samples in the data. 
n.marker 
a numeric value, the number of markers to use in bootstrapping. Default is the total number of markers. 
hf1 
h and f values to calculate main effect, organized as a matrix, with columns (k, h, f), k = 2 to 3. Needed when 
hf2 
h and f values to calculate interaction associations, organized as a matrix, with columns (k, h, f), k = 2 to 9. Needed when 
... 
graphical parameters. 
This function evaluates the input W values of main or interaction effects using a set of null Y by the Wtest
, and the evaluation is performed in several bootstrap samples to achieve fast and stable output. The W histogram and its theoretical Chisquared distribution density with f degrees of freedom are plotted indexed by k. Close overlaying of the histogram and the probability density curve indicates that the estimated h and f give a good test statistic probability distribution.
Rui Sun, Maggie Haitian Wang
Maggie Haitian Wang, Rui Sun, Junfeng Guo, Haoyi Weng, Jack Lee, Inchi Hu, Pak Sham and Benny C.Y. Zee (2016). A fast and powerful Wtest for pairwise epistasis testing. Nucleic Acids Research. doi:10.1093/nar/gkw347.
1 2 3 4 5 6  data(diabetes.geno)
# Please note that parameter B is recommended to be greater than 400.
hf1 < hf(data = diabetes.geno, w.order = 1, B = 100)
hf2 < hf(data = diabetes.geno, w.order = 2, B = 50)
w.diagnosis(diabetes.geno, w.order = 1, n.rep = 100, hf1 = hf1, main=NULL, xlab=NULL, ylab=NULL)
w.diagnosis(diabetes.geno, w.order = 2, n.rep = 100, hf2 = hf2, main=NULL, xlab=NULL, ylab=NULL)

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