gsnca_stat: Test statistics of Gene Sets Net Correlation Analysis (GSNCA)

In hui-sheen/MetaGSCA: Meta-analysis of Gene Set differential Co-expression Analysis

Test statistics of Gene Sets Net Correlation Analysis (GSNCA)

Description

Derive distance statistics by solving eigenvector of two pairise correaltion matrix.

Usage

gsnca_stat(objt1, objt2, cor.method = "pearson")

Arguments

objt1	dataset for condition 1, genes in columns
objt2	dataset for condition 2, genes in columns
cor.method	correlation coefficient method, the same as in function cor

Value

L1-norm distance between two weight vectors

See Also

[gsnca_p()] for the external function that calls on the current function and returns permutation p-statistic.

Examples

data(meta)
BRCA <- datasets[['BRCA']]
N <- ncol(BRCA)
n1 <- floor(N/2)
objt1 <- t(BRCA[1:min(66,nrow(BRCA)),1:n1])
objt2 <- t(BRCA[1:min(66,nrow(BRCA)),(n1+1):N])
gStat.res <- gsnca_stat(objt1,objt2)

hui-sheen/MetaGSCA documentation built on April 9, 2022, 7:24 p.m.