NormalyzerStatistics: Class representing a dataset for statistical processing in...

In ComputationalProteomics/NormalyzerDE: Evaluation of normalization methods and calculation of differential expression analysis statistics

Class representing a dataset for statistical processing in NormalyzerDE

Description

Is initialized with an annotation matrix, a data matrix and a design data frame. This object can subsequently be processed to generate statistical values and in turn used to write a full matrix with additional statistical information as well as a graphical report of the comparisons.

Usage

NormalyzerStatistics(experimentObj, logTrans = FALSE)

NormalyzerStatistics(experimentObj, logTrans = FALSE)

Arguments

experimentObj	Instance of SummarizedExperiment containing matrix and design information as column data
logTrans	Whether the input data should be log transformed

Value

nds Generated NormalyzerStatistics instance

Slots

annotMat

Matrix containing annotation information

dataMat

Matrix containing (normalized) expression data

filteredDataMat

Filtered matrix with low-count rows removed

designDf

Data frame containing design conditions

filteringContrast

Vector showing which entries are filtered (due to low count)

pairwiseCompsP

List with P-values for pairwise comparisons

pairwiseCompsFdr

List with FDR-values for pairwise comparisons

pairwiseCompsAve

List with average expression values

pairwiseCompsFold

List with log2 fold-change values for pairwise comparisons

contrasts

Spot for saving vector of last used contrasts

condCol

Column containing last used conditions

batchCol

Column containing last used batch conditions

Examples

data(example_stat_summarized_experiment)
nst <- NormalyzerStatistics(example_stat_summarized_experiment)

ComputationalProteomics/NormalyzerDE documentation built on Sept. 18, 2023, 9:15 p.m.