get_scr_mat: Determine screening matrix for CFGL by testing differential...

In Yafei611/CFGL: An adaptive procedure for inferring condition-specific gene co-expression network

Description

The function estimates differences between 2 precision matrixes. Then a multiple testing procedure with false discovery rate control will be applied to determine different entries between 2 matrixes. The testing result will be turned into a binary matrix which can be used as screening matrix for CFGL.

Usage

get_scr_mat(expr1, expr2, s = NULL, s.seq = seq(0.2, 2, 0.2), alpha = 0.4,
  verbose = F)

Arguments

expr1	A n*p matrix or data frame of normalized gene expression data. The rows correspond samples (n), the columns correspond genes (p).
expr2	The second gene expression data, should be in the same format, size as expr1.
s	The tuning parameter for matrixes differences estimation, leave it as NULL to automatically select.
s.seq	The candidates for s selection.
alpha	Prespecified level of false discovery rate. A relatively loose criterion is suggested for determines screening matrix.
verbose	Set verbose to TURE to show details of s selection.

Details

Please refer Yin et.al (2016). Testing differential networks with applications to the detection of gene-gene interactions. Biometrika(2015),pp. 1-20

Yafei611/CFGL documentation built on May 25, 2019, 2:23 p.m.