Create a sampleMap from an experiment list and phenoData dataframe

This function helps create a sampleMap in preparation of a MultiAssayExperiment object. This especially useful when the sample identifiers are not very different, as in the case of TCGA barcodes. An idConverter function can be provided to truncate such sample identifiers and obtain patient identifiers.

Usage

generateMap(
  experiments,
  colData,
  idConverter = identity,
  sampleCol,
  patientCol,
  ...
)

Arguments

experiments: A named list of experiments compatible with the MultiAssayExperiment API
colData: A data.frame of clinical data with patient identifiers as rownames
idConverter: A function to be used against the sample or specimen identifiers to match those in the rownames of the colData (default NULL)
sampleCol: A single string indicating the sample identifiers column in the colData dataset
patientCol: A single string indicating the patient identifiers in colData, "row.names" extracts the colData row names
...: Additonal arguments to pass to the 'idConverter' function.

Value

A DataFrame class object of mapped samples and patient identifiers including assays

Author

M. Ramos, M. Morgan, L. Schiffer

Examples

## Minimal example
expList <- list(assay1 = matrix(1:6, ncol = 2L,
        dimnames = list(paste0("feature", 1:3), c("A-J", "B-J"))),
    assay2 = matrix(1:4, ncol = 2,
        dimnames = list(paste0("gene", 1:2), c("A-L", "B-L"))))

## Mock colData
myPheno <- data.frame(var1 = c("Yes", "No"), var2 = c("High", "Low"),
    row.names = c("a", "b"))

## A look at the identifiers
vapply(expList, colnames, character(2L))
#>      assay1 assay2
#> [1,] "A-J"  "A-L" 
#> [2,] "B-J"  "B-L" 
rownames(myPheno)
#> [1] "a" "b"

## Use 'idConverter' to correspond sample names to patient identifiers
generateMap(expList, myPheno,
    idConverter = function(x) substr(tolower(x), 1L, 1L))
#> DataFrame with 4 rows and 3 columns
#>      assay     primary     colname
#>   <factor> <character> <character>
#> 1   assay1           a         A-J
#> 2   assay1           b         B-J
#> 3   assay2           a         A-L
#> 4   assay2           b         B-L