NWA: An S4 class for NetWork Analysis on high-throughput data

In CityUHK-CompBio/HTSanalyzeR2: HTSanalyzeR2: An R package for functional annotation, network analysis and time series analysis of high-throughput data

Description

This class includes a series of methods to do network analysis for high-throughput data.

Usage

NWA(pvalues, phenotypes = as.numeric(), interactome = NA)

Arguments

pvalues	A numeric or integer vector of pvalues named by gene identifiers.
phenotypes	A numeric or integer vector of phenotypes named by gene identifiers. When it is available, nodes in identified subnetwork would be coloured by it (red:+, blue:- as default). Otherwise, all nodes in the subnetwork would have no difference.
interactome	An object of class igraph.

Value

This function will create a new object of class 'NWA'.

Slots

fdr

One parameter for BioNet to score nodes in the interactome.

result

A list consisting of subnetwork module identified by BioNet and a vector of labels for nodes of the subnetwork module.

summary

A list of summary information for pvalues, phenotypes, interactome and result.

preprocessed

A logical value specifying whether or not input data has been preprocessed.

See Also

preprocess, analyze, summarize, interactome, report

Examples

library(org.Hs.eg.db)
library(GO.db)
## load data for network analyses
data(d7)
pvalues <- d7$neg.p.value
names(pvalues) <- d7$id

## define phenotypes if you want to color nodes by it, otherwise ignore it!
phenotypes <- as.vector(d7$neg.lfc)
names(phenotypes) <- d7$id

## Example1: create an object of class 'NWA' with phenotypes
nwa <- NWA(pvalues=pvalues, phenotypes=phenotypes)

## Example2: create an object of class 'NWA' without phenotypes
nwa <- NWA(pvalues=pvalues)

CityUHK-CompBio/HTSanalyzeR2 documentation built on Dec. 3, 2020, 2:35 a.m.