makeCalls.ihc {PCAPAM50}

Make a Conventional PAM50 Intrinsic Subtype Calls

Description

This function processes clinical and preprocessed PAM50 expression data to form an estrogen receptor (ER)-balanced set based on IHC classification. The ER-balanced set is created by distinguishing between ER-negative and ER-positive cases, and it produces conventional PAM50 intrinsic subtype calls.

Usage

makeCalls.ihc(df.cln, seed=118, mat, inputDir=NULL)

Arguments

df.cln

Data frame of clinical data; It should include the columns 'PatientID' and 'IHC'.

seed

Seed for random number generation to ensure reproducibility. Default is 118.

mat

Matrix of preprocessed PAM50 expression data.

inputDir

Directory for output files.If NULL, a subdirectory named "Calls.PAM50" within the temporary directory will be used.

Value

Returns a list containing:

Int.sbs

Data frame with integrated subtype and clinical data.

score.fl

Data frame with scores from subtype predictions.

mdns.fl

Data frame with median values for each gene in the ER-balanced set.

SBS.colr

Colors associated with each subtype from the prediction results.

outList

Detailed results from subtype prediction functions.

See Also

prcomp, merge, set.seed

Examples

  data_path <- system.file("extdata", "Sample_IHC_PAM_Mat.Rdat", package = "PCAPAM50")
  load(data_path) # Loads Test.ihc and Test.matrix


  # Prepare the data
  Test.ihc$ER_status <- rep("NA", length(Test.ihc$PatientID))
  Test.ihc$ER_status[grep("^L",Test.ihc$IHC)] = "pos"
  Test.ihc$ER_status[-grep("^L",Test.ihc$IHC)] = "neg"
  Test.ihc <- Test.ihc[order(Test.ihc$ER_status, decreasing = TRUE),]
  Test.matrix <- Test.matrix[, Test.ihc$PatientID]


  df.cln <- data.frame(PatientID = Test.ihc$PatientID, IHC = Test.ihc$IHC, stringsAsFactors = FALSE)


  

  # Call the function
  result <- makeCalls.ihc(df.cln=df.cln, seed = 118, mat = Test.matrix, inputDir=NULL)