anota2seqGetCovariates: Accessor for the 'phenoVec' and 'batchVec' slots of an...

In ChrOertlin/anota2seq: Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq

Description

Retrieve from an Anota2seqDataSet the covariate(s) to be used in the APV model i.e. the annotation of the samples according to their treatments and batch (when provided).

Usage

anota2seqGetCovariates(object)

## S4 method for signature 'Anota2seqDataSet'
anota2seqGetCovariates(object)

Arguments

object

An Anota2seqDataSet.

Value

A list of 2 elements named "phenoVec" and "batchVec" containing the corresponding covariates to be used for the analysis.

See Also

Anota2seqDataSet-class

Examples

data(anota2seq_data)
# Initialize Anota2seqDataSet
Anota2seqDataSet <- anota2seqDataSetFromMatrix(
    dataP = anota2seq_data_P[1:100,],
    dataT = anota2seq_data_T[1:100,],
    phenoVec = anota2seq_pheno_vec,
    batchVec = c(1, 2, 3, 4, 1, 2, 3, 4),
    dataType = "RNAseq",
    normalize = TRUE)
# Run analysis of differential translation
Anota2seqDataSet <- anota2seqAnalyze(Anota2seqDataSet, 
                                     analysis = "translation")
covariates <- anota2seqGetCovariates(Anota2seqDataSet)
covariates
# $phenoVec
# [1] "ctrl"      "ctrl"      "ctrl"      "ctrl"      "treatment" "treatment"
# [7] "treatment" "treatment"
# 
# $batchVec
# [1] "1" "2" "3" "4" "1" "2" "3" "4"

ChrOertlin/anota2seq documentation built on Aug. 4, 2021, 2:17 p.m.