View source: R/DEGsExtraction.R
DEGsExtraction | R Documentation |
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.
DEGsExtraction( expressionMatrix, labels, pvalue = 0.05, lfc = 1, cov = 1, nmax = 1, multiDegsMethod = "cov", number = Inf, CV = FALSE, numFolds = 5 )
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 establishes a minimum number of pair of classes combination in which exists differential expression to consider a genes as expressed genes. |
nmax |
This value only works when there are more than two classes in the labels. NMAX indicates the maximum number of DEGs selected for each class pair comparison. |
multiDegsMethod |
Select the multiclass extraction method for the process: cov or nmax |
number |
The maximum number of desired genes as output of limma. As default, the function returns all the extracted DEGs with the selected parameters. |
CV |
A boolean value that has to be setted to TRUE if the user would to run a Cross-Validation DEGs extraction process. |
numFolds |
This parameter indicates the number of folds for the Cross-Validation process. |
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.
dir <- system.file("extdata", package="KnowSeq") load(paste(dir,"/expressionExample.RData",sep = "")) expressionMatrix <- calculateGeneExpressionValues(countsMatrix,myAnnotation, genesNames = TRUE) DEGsInformation <- DEGsExtraction(expressionMatrix, labels, lfc = 2.0, pvalue = 0.01, number = Inf) topTable <- DEGsInformation$Table DEGsMatrix <- DEGsInformation$DEGsMatrix
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