A benchmark type function to test a complete process of FBN model All sub time series must contain the same number of timepoints Step 3, identify significantly expressed genes, which are strongly related with the samples / study purposes

Source: R/FBNBioinformatics.R

A benchmark type function to test a complete process of FBN model All sub time series must contain the same number of timepoints Step 3, identify significantly expressed genes, which are strongly related with the samples / study purposes

identifyDifferentiallyExpressedGenes(
  orderSampleTimeSeries,
  cutOffInduction = 1,
  cutOffRepression = 1,
  majority = 7,
  needLog2scale = FALSE,
  probesetGeneNameMappings = NULL,
  nameTab = "RMA"
)

Arguments

orderSampleTimeSeries

A sorted time series data, which is the output of the method reorderSampleTimeSeries

cutOffInduction

a threshold that identify genes as folds. If the cutOffInduction is 2, the differential genes are identified based on 2 folds

cutOffRepression

a threshold that identify genes as folds. If the cutOffRepression is 2, the differential genes are identified based on 2 folds

majority

A criteria that make a gene as differential

needLog2scale

If it is true, then all gene values will be processed using log2

probesetGeneNameMappings

gene mapping file