coexpr: Identification of gene pairs coexpressed in at least one of...

In diffcoexp: Differential Co-expression Analysis

Description

This function identifies gene pairs coexpressed in at least one of two conditions.

Usage

coexpr(exprs.1, exprs.2, r.method = c("pearson", "spearman")[1],
  q.method = c("BH", "holm", "hochberg", "hommel", "bonferroni", "BY", "fdr",
  "none")[1], rth = 0.5, qth = 0.1)

Arguments

exprs.1	a SummarizedExperiment, data frame or matrix for condition 1, with gene IDs as rownames and sample IDs as column names.
exprs.2	a SummarizedExperiment, data frame or matrix for condition 2, with gene IDs as rownames and sample IDs as column names.
r.method	a character string specifying the method to be used to calculate correlation coefficients. It is passed to the cor function of the WGCNA package.
q.method	a character string specifying the method for adjusting p values. It is passed to the p.adjust function of the stats package.
rth	the cutoff of absolute value of correlation coefficients; must be within [0,1].
qth	the cutoff of q-value (adjusted p value); must be within [0,1].

Value

a data frame containing gene pairs that are coexpressed in at least one of the conditions with the criteria that absolute value of correlation coefficient is greater than rth and q value less than qth. It has the following columns:

Gene.1	Gene ID
Gene.2	Gene ID
cor.1	correlation coefficients under condition 1
cor.2	correlation coefficients under condition 2
cor.diff	difference between correlation coefficients under condition 2 and condition 1
p.1	p value under null hypothesis that correlation coefficient under condition 1 equals to zero
p.2	p value under null hypothesis that correlation coefficient under condition 2 equals to zero
p.diffcor	p value under null hypothesis that difference between two correlation coefficients under two conditions equals to zero using Fisher's r-to-Z transformation
q.1	adjusted p value under null hypothesis that correlation coefficient under condition 1 equals to zero
q.2	adjusted p value under null hypothesis that correlation coefficient under condition 2 equals to zero
q.diffcor	adjusted p value under null hypothesis that the difference between two correlation coefficients under two conditions equals to zero using Fisher's r-to-Z transformation

Examples

data(gse4158part)
allowWGCNAThreads()
res=coexpr(exprs.1 = exprs.1, exprs.2 = exprs.2, r.method = "spearman")
#The result is a data frames.
str(res)

diffcoexp documentation built on Nov. 8, 2020, 7:36 p.m.