DiffHub {dhga}

Differential Hub status of the genes in a gene co-expression network

Description

The function returns hub status of each gene in a gene co-expression network under two contrasting conditions

Usage

DiffHub(x,y,m1,m2,s,beta,alpha, plot=TRUE)

Arguments

x

x is a data frame of gene expression values where rows represent genes and columns represent samples/time point under stress condition.

y

y is a data frame of gene expression values where rows represent genes and columns represent samples/time points under control condition.

m1

m1 is a scalar representing sample size and is less than or equal to number of columns in x.

m2

m2 is a scalar representing sample size and is less than or equal to number of columns in y.

s

s is a scalar representing number of times each of the m samples will be resampled.

beta

beta is a soft threshold parameter determined from the scale free property of biological networks (GCN).

alpha

alpha is a scalar representing statistical level of significance. Default is alpha=0.0001

plot

plot is a character representing whether the hubplot can be drawn (TRUE) or not (FALSE).

Value

The function returns a list with two components. First component returns the list of genes along with their hub status. Second component gives a table containing number of genes under different categories of hubs viz. housekeeping, unique to stress and unique to normal. The function also returns a venn plot of hub genes and unique hub genes under two conditions.

Author(s)

Samarendra Das and Baidya Nath Mandal

Examples

data(rice_salt)
data(rice_normal)
DiffHub(rice_salt,rice_normal,18,18,80, 6, alpha=0.0001, plot=TRUE)