GSEPD_PCA_Spec {rgsepd} | R Documentation

## Specialized PCA Plot

### Description

After processing the pipeline, users may want to have further PCA figures generated. This function takes a completed GSEPD object and generates informative figures. This function includes parameters to specify a particular GO-Term of interest.

### Usage

    GSEPD_PCA_Spec(GSEPD, GOT, MDATA = NULL, customColors=FALSE)

### Arguments

`GSEPD` | The master GSEPD object, post-processed.
`GOT` | The GO-Term you'd like to specifically analyse. It should be found in the .MERGE file.
`MDATA` | Optionally, pass in the .MERGE dataset, if missing, we'll try to read the already-processed file from the output directory. This option exists because reading that file repeatedly is quite slow, so you're recommended to read it in once in advance if you intend on making more than a couple GO-Term specific plots.
`customColors` | a boolean value, when FALSE, default behavior is to color points to match the test conditions. When TRUE, use sampleMeta$CustomColor column for a sample-by-sample user specification. This behavior disables the built-in legend.

### Value

No return value. Generates files.

### Note

This function uses either princomp() or prcomp() as neccesary, depending on sample count vs gene count.

### See Also

GSEPD_PCA_Plot

### 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

      GOT <- "GO:0012345" # specify a GO Term you'd like to review

      #it should be present in the MERGE file.
      MergeFile <- list.files(G$Output_Folder, pattern="MERGE")[1]
      MDATA<-read.csv(sprintf("%s%s%s", G$Output_Folder, .Platform$file.sep, MergeFile),
          as.is=TRUE,header=TRUE)

      GOT=MDATA$category[1] #choose a GO term that is definitely in the output data.

      GSEPD_PCA_Spec(G, GOT,MDATA=MDATA)

[Package rgsepd version 1.16.0 Index]