mra: Modular Reponse Analysis function

In bioinfo-ircm/aiMeRA: Modular Response Analysis for the quantitative analysis of connectivity in biological networks

Description

Calculation of connectivity coefficients between modules in a biological network using modular response analysis.

Usage

mra(tab,matp,check=TRUE,Rp=FALSE)

Arguments

tab	A data.frame containing experimental data in a specific format (see details).
matp	The perturbation matrix. Names of modules (rows) and perturbations (columns) must correspond to names of rows and columns in tab.
check	Logical. Should the dataset and perutbation matrix be checked for input errors?
Rp	Logical. TRUE if “'tab“' is the calcuated global response matrix.

Details

It assumes that one perturbation must affect only one biological module of the network. This is specified as binary values in the perturbation matrix. It also assumes that row names in data tables are the names of biological modules and column names are the the names of perturbations.

Value

A list containing the connectivity map, the local responses matrix, the network responses matrix to perturbations and the basal line for all modules.

Examples

#It creates the connectivity map between 2 transcriptional nuclear coregulators
#(RIP140 and LCoR) and estrogen receptor alpha transcriptional activity reported by
#a luciferase gene. q-PCR data is stored in the package files used below in the function data.setup
#The model is obtained using the E2 stimulated condition.

data=data.setup(list(estr1_A,estr1_B,estr2_A,estr2_B,estr3_A,estr3_B))
sd.mean=data2sdmean(data)
rules=c("Et->Luciferase","E2+siRIP140->RIP140","E2+siLCoR->LCoR","E2->0")
matp=read.rules(rules)
mra(sd.mean$mean,matp,check=TRUE)

bioinfo-ircm/aiMeRA documentation built on Oct. 1, 2021, 8:11 a.m.