st6 {corTest}R Documentation

Test Differential Correlation Using st6 Method

Description

Compute p-value for the equal correlation test with another way to combine Spearman corrleaion and percentage bend correlation based on a multiple logistic regression model corresponding to two independent groups

Usage

st6(x1, z1, x0, z0)

Arguments

x1

a numeric vector

z1

a numeric vector with same length as x1

x0

a numeric vector

z0

a numeric vector with same length as x0

Value

A list with 3 elements:

u

the vector of Fisher score.

pval

p-value of test for testing if correlation between x1 and z1 is the same as that between x0 and z0

cov_u

covariance matrix for u.

Author(s)

Danyang Yu <dyu33@jhu.edu>, Weiliang Qiu <weiliang.qiu@gmail.com>

References

Danyang Yu, Zeyu Zhang, Kimberly Glass, Jessica Su, Dawn L. DeMeo, Kelan Tantisira, Scott T. Weiss, Weiliang Qiu(corresponding author). New Statistical Methods for Constructing Robust Differential Correlation Networks to characterize the interactions among microRNAs. Scientific Reports 9, Article number: 3499 (2019)

Examples

x1 = ghdist(n = 100, g = 0.2, h = 0.2)
x0 = ghdist(n = 100, g = 0.2, h = 0.2)
z1 = x1 + ghdist(n = 100, g = 0.2, h = 0.2)
z0 = x0 + ghdist(n = 100, g = 0.2, h = 0.2)
res = st6(x1, z1, x0, z0)
print(res)

[Package corTest version 1.0.7 Index]