DataTableWithClasses: constructor of the DataTableWithClasses class

In elqumsan/RNAseqMVA: Application of Multivariate Analysis methods to RNA-seq Data

Description

This class contains count tables (typically used to represent expression profiles in RNA-seq analysis) documented with a Pheno table (description of each sample) and completed with some additional fields for convenience: sample names, gene names, ...

Usage

DataTableWithClasses(dataTable, phenoTable, dataType, parameters)

Arguments

dataTable	a data.frame with one row per feature (e.g. gene) and one column per sample.
phenoTable	a data frame describing each sample: one row per sample and one column per attribute of a sample.
parameters	global and specific parameters for the analysis of this recountID
dataType="raw	counts" data type, free text (e.g. raw counts, log2-transformed counts, log2 normalised counts ...).

Value

it is create object that is belonge to DataTableWithClasses class that means it would have the follwing attributes

• dataTable: is count table that is contains one raw per feature (e.g. gene) and one column per individual (e.g. sample)

• phenoTable: that is description table for all individuals whereas that erach raw is individual (sample) and each column is the itemize for such individuals

• dataType: that is deemed feature type whereas we have filtered, scaled, log2-norm, PCs of log2norm and so on. to inspect the impact of pre-processing procedures with NGS data.

• parameters = that is all the accompanying parameters to recount study case

• classColumn: that is indeed refers to type of the outcome column.

• nbGenes: that is whole number of features.

• sampleNames: that is names of individuals that are included in the new object.

• featureNames: the names of each genes in the count table that will be involved in new object.

• classLabels: that is the class labels for all the samples in the relatedness object.

• classNames: that is the names of all classes included in the relatedness object.

• nbClasses: that is the overall number of the classes involved in the relatedness object.

• classProperities: that is the data.frame composed of two columns one for the class name, number of samples in each class, train size per class

• samplesPerClass: such paraperter are involved in classProperities.

• classFrequencies: such parameter means the ratio of certain samples for somehow class so as to the whole samples into the dataTable.

• randExpectedHitRate: it is corss product for the classFrequensies .

• randExpectedMisclassificationRate: it is 1 - randExpectedHitRate.

• sampleColors: such parameter for visualisation of the sample by putting some useful colors.

• classColors: such parameter for puting special color for each class involved in analysis.

Author(s)

Mustafa AbuElQumsan and Jacques van helden

elqumsan/RNAseqMVA documentation built on March 10, 2021, 8:10 a.m.