coptest: Two sample test for empirical copula.

In ymatts/RoDiCE: Robust differential co-expression test by copula

Description

Two sample test for empirical copula.

Usage

coptest(x1, x2, nperm = 100, approx = TRUE)

Arguments

x1	Numeric matrix. Samples in row and variables in column
x2	Numeric matrix. The same with x1.
nperm	The number of permutation.
approx	Logical. If 'approx=TRUE', p-value will be approximated using generalized Parato distribution. Otherwise, no approximation of p-value.

Value

List of three components:

• pval - p-value

• stat - test statistics based on Cramér–von Mises test statistic

• null - null distribution from randomization procedure

Author(s)

Yusuke MATSUI

References

Yusuke MATSUI et al.(2020) RoDiCE: Robust differential protein co-expression analysis for cancer complexome (submitted).

Clerk DJ et al.(2019) Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.Cell;179(4),964-983 e931.

Examples

data(ccrcc.pbaf) # example data from clear renal cell carcinoma(clerk et al.2019)
data(corum.hsp.pbaf)
tumor = ccrcc.pbaf$tumor # 110 samples and 10 proteins from PBAF complex
normal = ccrcc.pbaf$normal # 84 samples and 10 proteins from PBAF complex

# multivariate copula test(more than three variables)
result = coptest(tumor,normal,nperm=100,approx=FALSE)
result$pval

ymatts/RoDiCE documentation built on Jan. 1, 2021, 1:45 p.m.