diggit-class: The diggit class

In diggit: Inference of Genetic Variants Driving Cellular Phenotypes

Description

This class stores parameters and results of the diggit algorithm

This function generates diggit class objects

Usage

diggitClass(expset = NULL, cnv = NULL, regulon = NULL, mindy = NULL,
  fcnv = NULL, mr = NULL, viper = NULL, aqtl = NULL,
  conditional = NULL)

Arguments

expset	ExpressionSet object or numeric matrix of expression data, with features in rows and samples in columns
cnv	Numeric matrix of CNV data
regulon	Regulon class object containing the transcriptional interactome
mindy	Regulon class object containing the post-translational interactome
fcnv	Vector of F-CNV p-values
mr	Vector of master regulator Z-score (NES)
viper	Numeric matrix of VIPER results
aqtl	Numeric matrix of aQTL p-values
conditional	List containing the conditional analysis results

Details

see diggit-methods for related methods

Value

Object of class diggit

Slots

expset:

ExpressionSet object containing the gene expression data

cnv:

Matrrix containing the CNV data

regulon:

Regulon object containing the transcriptional interactome

mindy:

Regulon object containing the post-translational interactome

fcnv:

Numeric vector containing the p-values for functional CNVs

mr:

Numeric vector of normalized enrichment scores for the MARINa analysis

viper:

Numeric matrix of normalized enrichment scores for the VIPER analysis

aqtl:

Numeric matrix of association p-values for the aQTL analysis

conditional:

List containing the conditional analysis results

Examples

data(gbm.expression, package="diggitdata")
data(gbm.aracne, package="diggitdata")
dobj <- diggitClass(expset=gbmExprs, regulon=gbmTFregulon)
print(dobj)

diggit documentation built on Nov. 8, 2020, 8:18 p.m.