non_nullcov: non_nullcov

In IntegratedJM: Joint Modeling of the Gene-Expression and Bioassay Data, Taking Care of the Effect Due to a Fingerprint Feature

Description

The non_nullcov function is called while fitting the model when the covariate is specified in the fitJM function. It returns a data.frame containing the results after fitting the model. The output of this function is also the output of the fitJM function.

Usage

non_nullcov(dat, responseVector, covariate, methodMultTest, data_type)

Arguments

dat	Contains the gene expression data matrix for all the genes - can be a matrix or an expression set.
responseVector	Vector containing the bio-activity data.
covariate	Vector of 0's and 1's, containing data about the fingerprint feature.
methodMultTest	Character string to specify the multiple testing method.
data_type	Binary, specifying the type of the parameter dat: 0 - expressionSet, 1 - matrix.

Details

Fits the model, adjusting for the covariate effect, using gls, calculates the correlation, p-values, adjusted p-values (based on the multiple testing method) and logratio from LRT and returns the required results.

Value

A data frame, containing the results of the model - same as the output of the fitJM function.

Examples

## Not run: 
non_nullcov(dat=gene_eset,responseVector=activity,covariate=fp,methodMultTest='fdr',data_type=0)

## End(Not run)

IntegratedJM documentation built on May 2, 2019, 2:44 p.m.