This function extract the p values for permutation approach performed using scanWGassociation function
permTest(x, method="minimum", K)An object of class 'permTest'.
'print' returns a summary indicating the number of SNPs analyzed, the number of valid SNPs (those non-Monomorphic and that pass the calling rate), the p value after Bonferroni correction, and the p values based on permutation approach. One of them is based on considering the empirical percentil for the minimum p values, and the another one on assuming that the minimum p values follow a beta distribution.
'plot' produces a plot of the empirical distribution for the minimum p values (histogram) and the expected distribution assuming a beta distribution. The corrected p value is also showed in the plot.
See examples for further illustration about all previous issues.
a required object of class 'WGassociation' with the attribute 'permTest'. See details
statistic used in the permutation test. The default is 'minimum' but 'rtp' (rank truncated product) is also available.
number of the K most significant p values from the total number of test performed (e.g number of SNPs) used to compute the rank truncated product. This argument is only required when method='rtp'. See references
This function extract the p values from an object of class 'WGassociation'. This object migth be obtained using the funcion called 'scanWGassociation' indicating the number of permutations in the argument 'nperm'.
Dudbridge F, Gusnanto A and Koeleman BPC. Detecting multiple associations in genome-wide studies. Human Genomics, 2006;2:310-317.
Dudbridge F and Koeleman BPC. Efficient computation of significance levels for multiple associations in large studies of correlated data, including genomewide association studies. Am J Hum Genet, 2004;75:424-435.
JR Gonzalez, L Armengol, X Sole, E Guino, JM Mercader, X Estivill, V Moreno. SNPassoc: an R package to perform whole genome association studies. Bioinformatics, 2007;23(5):654-5.
scanWGassociation
library(SNPassoc)
data(asthma, package = "SNPassoc")
asthma.s <- setupSNP(data=asthma, colSNPs=7:ncol(asthma), sep="")
ans <- WGassociation(casecontrol, data=asthma.s)
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