Added an to remove genes with 0 expression across all cells from the …

…GEX input

DESCRIPTION

@@ -1,12 +1,12 @@
 Package: SCORPION
 Type: Package
 Title: Single Cell Oriented Reconstruction of PANDA Individual Optimized Networks
-Version: 1.0.1
+Version: 1.0.2
 Authors@R: c(person("Daniel","Osorio", email = "[email protected]", role = c("aut","cre"), comment = c(ORCID = "0000-0003-4424-8422")),
   person("Marieke L.","Kuijjer", email = "[email protected]", role = c("aut"), comment = c(ORCID = "0000-0001-6280-3130")))
 Description: Constructs gene regulatory networks from single-cell gene expression data using the PANDA (Passing Attributes between Networks for Data Assimilation) algorithm.
 License: GPL-3
 Encoding: UTF-8
 LazyData: true
 Imports: cli, methods, irlba, igraph, RANN, Matrix, pbapply, RhpcBLASctl
-RoxygenNote: 7.1.2
+RoxygenNote: 7.2.3

R/makeSuperCells.R

@@ -45,6 +45,7 @@ makeSuperCells <- function(X,
     colnames(X) <- paste("cell", 1:N.c, sep = "_")
   }
 
+  X <- X[rowSums(X) > 0,]
   keep.genes    <- setdiff(rownames(X), genes.exclude)
   X             <- X[keep.genes, ]
 
@@ -254,7 +255,7 @@ makeSuperCells <- function(X,
       stop("weights must be the same length as groups or NULL in case of unweighted averaging")
     }
     M.AV <- Matrix::sparseMatrix(i = i, j = j, x = weights[i])
-    GE <- X %*% M.AV
+    GE <- GE %*% M.AV
 
     weighted_supercell_size <-
       unlist(lapply(

R/scorpion.R

@@ -17,7 +17,8 @@
 #' @param zScaling Boolean to indicate use of Z-Scores in output. False will use [0,1] scale.
 #' @param showProgress Boolean to indicate printing of output for algorithm progress.
 #' @param randomizationMethod Method by which to randomize gene expression matrix. Default "None". Must be one of "None", "within.gene", "by.genes". "within.gene" randomization scrambles each row of the gene expression matrix, "by.gene" scrambles gene labels.
-#' @param scaleByPresent Boolean to indicate scaling of correlations by percentage of positive samples
+#' @param scaleByPresent Boolean to indicate scaling of correlations by percentage of positive samples.
+#' @param filterExpr Boolean to indicate wheter or not to remove genes with 0 expression across all cells from the GEX input.
 #' @return A list of matrices describing networks achieved by convergence with PANDA algorithm.
 #' @examples
 #' # Loading example data
@@ -102,11 +103,14 @@ scorpion <- function(tfMotifs = NULL,
                      zScaling = TRUE,
                      showProgress = TRUE,
                      randomizationMethod = 'None',
-                     scaleByPresent = FALSE) {
+                     scaleByPresent = FALSE,
+                     filterExpr = FALSE) {
 
   cli::cli_h1('SCORPION')
 
-  gexMatrix <- gexMatrix[rowSums(gexMatrix) > 0,]
+  if(isTRUE(filterExpr)){
+    gexMatrix <- gexMatrix[rowSums(gexMatrix) > 0,]
+  }
   gexMatrix <- makeSuperCells(X = gexMatrix, gamma = gammaValue, n.pc = nPC, fast.pca = FALSE)
 
   if(is.null(ppiNet) & is.null(tfMotifs)){