limmaDEGsExtraction {KnowSeq} | R Documentation

## limmaDEGsExtraction performs the analysis to extract the Differentially Expressed Genes (DEGs) among the classes to compare.

### Description

The function performs the analysis to extract the Differentially Expressed Genes (DEGs) among the classes to compare. The number of final DEGs can change depending on the p-value and the LFC indicated by parameters of the function. Furthermore, the function detects if the number of classes are greater than 2 to perform a multiclass DEGs analysis.

### Usage

    limmaDEGsExtraction(expressionMatrix, labels, pvalue = 0.05, lfc = 1,
      cov = 1, number = Inf, svaCorrection = FALSE, svaMod)

### Arguments

`expressionMatrix` | The expressionMatrix parameter is an expression matrix or data.frame that contains the genes in the rows and the samples in the columns.
`labels` | A vector or factors that contains the labels for each of the samples in the expressionMatrix parameter.
`pvalue` | The value of the p-value which determines the DEGs. If one or more genes have a p-value lower or equal to the selected p-value, they would be considered as DEGs.
`lfc` | The value of the LFC which determines the DEGs. If one or more genes have a LFC greater or equal to the selected LFC, they would be considered as DEGs.
`cov` | This value only works when there are more than two classes in the labels. This parameter stablishs a minimum number of pair of classes combination in which exists differential expression to consider a genes as expressed genes.
`number` | The maximum number of desired genes as output of limma. As default, the function returns all the extracted DEGs with the selected parameters.
`svaCorrection` | A logical variable that represents if the model for limma is calculated or indicated by parameter from the output of `batchEffectRemoval` function by using sva method.
`svaMod` | The model calculated by `batchEffectRemoval` function by using sva method.

### Value

A list that contains two objects. The table with statistics of the different DEGs and a reduced expression matrix which contains the DEGs and the samples.

### Examples

    dir <- system.file("extdata", package="KnowSeq")
    load(paste(dir,"/expressionExample.RData",sep = ""))

    expressionMatrix <- calculateGeneExpressionValues(countsMatrix,myAnnotation, genesNames = TRUE)

    DEGsInformation <- limmaDEGsExtraction(expressionMatrix, labels, lfc = 2.0,
    pvalue = 0.01, number = Inf)

    topTable <- DEGsInformation$Table

    DEGsMatrix <- DEGsInformation$DEGsMatrix

[Package KnowSeq version 1.0.0 Index]