GSEPD_PullDEG: Pull Differentially Expressed Genes

In kstammits/rgsepd: Gene Set Enrichment / Projection Displays

Pull Differentially Expressed Genes

Description

After processing, if you want to easily access the differentially expressed transcript listing, this function will read in the default generated files, and apply filters as specified by the GSEPD master object (default p-values).

Usage

GSEPD_PullDEG(GSEPD, PTHRESH)

Arguments

GSEPD	The master object should have been processed already such that differentially expressed genes are readily available.
PTHRESH	Specify the degree of stringency.

Value

Returns a vector of ID#, suitable to row-subsetting of the finalCounts table.

Examples

  data("IlluminaBodymap")
  data("IlluminaBodymapMeta")
  set.seed(1000) #fixed randomness
  isoform_ids <- Name_to_RefSeq(c("HIF1A","EGFR","MYH7","CD33","BRCA2"))
  rows_of_interest <- unique( c( isoform_ids ,
                                 sample(rownames(IlluminaBodymap),
                                        size=2000,replace=FALSE)))
  G <- GSEPD_INIT(Output_Folder="OUT",
                finalCounts=round(IlluminaBodymap[rows_of_interest , ]),
                sampleMeta=IlluminaBodymapMeta,
                COLORS=c("green","black","red"))
  G <- GSEPD_ChangeConditions( G, c("A","B")) #set testing groups first!   
  G <- GSEPD_Process( G ) #have to have processed results to plot them
  
  Significant_Genes <- GSEPD_PullDEG(G, PTHRESH=0.0250)
  #then do more with these identifiers:
  print(Significant_Genes)
  # GSEPD_Heatmap(G, genes= Significant_Genes )
  

kstammits/rgsepd documentation built on Oct. 13, 2022, 6:43 p.m.