easyDifferentialGeneCoexpression {easyDifferentialGeneCoexpression} | R Documentation |
Function that computes the differential coexpression of a list of probesets in a specific dataset and returns the most significant pairs
Description
Function that computes the differential coexpression of a list of probesets in a specific dataset and returns the most significant pairs
Usage
easyDifferentialGeneCoexpression(
list_of_probesets_to_select,
GSE_code,
featureNameToDiscriminateConditions,
firstConditionName,
secondConditionName,
batchCorrection = TRUE,
verbose = FALSE
)
Arguments
list_of_probesets_to_select |
list of probesets for which the differential coexpression should be computed |
GSE_code |
GEO accession code of the dataset to analyze |
featureNameToDiscriminateConditions |
name of the feature of the dataset that contains the two conditions to investigate |
firstConditionName |
name of the first condition in the feature to discriminate (for example, "healthy") |
secondConditionName |
name of the second condition in the feature to discriminate (for example, "cancer") |
batchCorrection |
says if the script should perform the batch correction with limma::removeBatchEffect() or not |
verbose |
prints all the intermediate message to standard output or not |
Value
a dataframe containing the significantly differentially co-expressed pairs of genes
Examples
probesetList <- c("200738_s_at", "217356_s_at", "206686_at")
verboseFlag <- "TRUE"
batchCorrection <- "TRUE"
signDiffCoexpressGenePairs <- easyDifferentialGeneCoexpression(probesetList,
"GSE3268", "description", "Normal", "Tumor", verboseFlag)
[Package easyDifferentialGeneCoexpression version 1.4 Index]