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 |
x0 |
a numeric vector |
z0 |
a numeric vector with same length as |
Value
A list with 3 elements:
u |
the vector of Fisher score. |
pval |
p-value of test for testing if correlation between |
cov_u |
covariance matrix for |
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)