Description Usage Arguments Details Value Note Author(s) References See Also Examples
Kolmogorov-Smirnov test for the return value of 'meta.TradPerm' and 'meta.MCPerm'.
1 2 3 4 |
Trad_data |
a matrix with more than one line, each line is the return value of function 'meta.TradPerm'(e.g. 'perm_case_11' of certain study, 'perm_Qp', 'perm_p' etc). |
MC_data |
a matrix with more than one line, each line is the return value of function 'meta.MCPerm'(e.g. 'perm_case_11' of certain study, 'perm_Qp', 'perm_p' etc). |
scatter_alpha |
numeric indicates k-s test p.value less 'scatter_alpha' to be plotted. Default value is 0.01. |
line_alpha |
numeric indicates the threshold value of k-s test significance. Default value is 0.001. |
scatter_col |
the color of sctter points which to be plotted. Default value is 'black'. |
line_col |
the color of the line. Default value is 'red'. |
xlab,ylab |
X axis label. Y axis label, default value is 'KS test p_value'. |
title |
the main title(on top),default value is "KS (Kolmogorov-Smirnov) test". |
Kolmogorov-Smirnov test for the return value(e.g. 'perm_case_11', 'perm_Qp' etc.) of 'meta.TradPerm' and 'meta.MCPerm' to test the corresponding form the whole. Just plotting p.value less the 'scatter_alpha' will more clear to see the number of no-corresponding data.
KS_p |
a numeric vector, p.value of K-S test. |
Parameter 'Trad_data' and 'MC_data' are matrix with more than one line.
Lanying Zhang and Yongshuai Jiang <jiangyongshuai@gmail.com>
The two-sided one-sample distribution comes via Marsaglia, Tsang and Wang (2003).
meta.MCPerm
,
meta.TradPerm
,
chisq.MCPerm
,
chisq.TradPerm
,
VS.Hist
,
VS.CDC
,
VS.QQ
VS.Allele.Hist
,
VS.Genotype.Hist
1 2 3 4 5 6 7 8 9 10 | ## write the return value 'perm_case_11','perm_Qp' or 'perm_p' of function 'meta.TradPerm'
# to file 'Trad_data.txt'
## write the return value 'perm_case_11','perm_Qp' or 'perm_p' of function 'meta.MCPerm'
# to file 'MC_data.txt'
## when all meta analysis run over, read the file to K-S test
## if the line of file is separated by '\t'
# Trad=read.table("Trad_data.txt",sep="\t",header=FALSE)
# MC=read.table("MC_data.txt",sep="\t",header=FALSE)
# VS.KS(Trad, MC)
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