extractSignatures new arguments

R/extractSignatures.R

@@ -6,6 +6,8 @@
 #'
 #' @param mat Input matrix of diemnsion nx96 generated by \code{\link{trinucleotideMatrix}}
 #' @param n decompose matrix into n signatures. Default NULL. Tries to predict best value for \code{n} by running NMF on a range of values and chooses based on cophenetic correlation coefficient.
+#' @param nrun Default 1. Number of runs to perform
+#' @param absolute Default FALSE. Returns absolute contribution per sample.
 #' @param plotBestFitRes plots consensus heatmap for range of values tried. Default FALSE
 #' @param parallel Default 4. Number of cores to use.
 #' @param pConstant A small positive value to add to the matrix. Use it ONLY if the functions throws an \code{non-conformable arrays} error
@@ -23,7 +25,7 @@
 #' @export
 
 
-extractSignatures = function(mat, n = NULL, plotBestFitRes = FALSE, parallel = 4, pConstant = NULL){
+extractSignatures = function(mat, n = NULL, nrun = 1, absolute = FALSE, plotBestFitRes = FALSE, parallel = 4, pConstant = NULL){
 
     #suppressPackageStartupMessages(require(NMF, quietly = TRUE))
     #transpose matrix
@@ -57,9 +59,9 @@ extractSignatures = function(mat, n = NULL, plotBestFitRes = FALSE, parallel = 4
 
     message(paste0('-Running NMF for factorization rank: ', n))
     if(!is.null(parallel)){
-      conv.mat.nmf = NMF::nmf(x = mat, rank = n, .opt = paste0('P', parallel), seed = 123456)
+      conv.mat.nmf = NMF::nmf(x = mat, rank = n, nrun = nrun, .opt = paste0('P', parallel), seed = 123456)
     }else{
-      conv.mat.nmf = NMF::nmf(x = mat, rank = n, seed = 123456)
+      conv.mat.nmf = NMF::nmf(x = mat, rank = n, nrun = nrun, seed = 123456)
     }
 
     #Signatures
@@ -70,6 +72,11 @@ extractSignatures = function(mat, n = NULL, plotBestFitRes = FALSE, parallel = 4
     #Contribution
     h = NMF::coef(conv.mat.nmf)
     colnames(h) = colnames(mat) #correct colnames (seems to be mssing with low mutation load)
+    #Absolute contributions per sample, exposures are not scaled
+    if (absolute == TRUE) {
+      h_absolute = h
+      rownames(h_absolute) = paste("Signature", 1:nrow(h_absolute), sep = "_")
+    }
     #For single signature, contribution will be 100% per sample
     if(n == 1){
       h = h/h
@@ -80,5 +87,10 @@ extractSignatures = function(mat, n = NULL, plotBestFitRes = FALSE, parallel = 4
     }
 
     message("-Finished in",data.table::timetaken(start_time))
-    return(list(signatures = w, contributions = h, nmfObj = conv.mat.nmf))
+    if (absolute == TRUE) {
+      return(list(signatures = w, contributions = h, absolute_contributions = h_absolute, nmfObj = conv.mat.nmf))
+    }
+    else {
+      return(list(signatures = w, contributions = h, nmfObj = conv.mat.nmf))
+    }
 }