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Reformat the use of withConsoleMastRedirect; A few UI bug fixes

Yichen Wang authored on 14/06/2022 17:30:54
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@@ -1,18 +1,20 @@
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-.myenv <- new.env(parent = emptyenv())
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-
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 #' Run GSVA analysis on a \linkS4class{SingleCellExperiment} object
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 #'
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 #' @param inSCE Input \linkS4class{SingleCellExperiment} object.
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 #' @param useAssay Indicate which assay to use. The default is "logcounts"
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-#' @param geneSetCollectionName Character. The name of the gene set collection to use.
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-#' parameter.
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-#' @param resultNamePrefix  Character. Prefix to the name the GSVA results which will be stored in the reducedDim slot of \code{inSCE}. The names of the output matrix will be \code{resultNamePrefix_Scores}. If this parameter is set to \code{NULL}, then "GSVA_geneSetCollectionName_" will be used. Default \code{NULL}.
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+#' @param geneSetCollectionName Character. The name of the gene set collection 
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+#' to use. 
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+#' @param resultNamePrefix  Character. Prefix to the name the GSVA results 
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+#' which will be stored in the reducedDim slot of \code{inSCE}. The names of the 
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+#' output matrix will be \code{resultNamePrefix_Scores}. If this parameter is 
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+#' set to \code{NULL}, then "GSVA_geneSetCollectionName_" will be used. Default 
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+#' \code{NULL}.
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 #' @param ... Parameters to pass to gsva()
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 #'
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-#' @return   A \link[SingleCellExperiment]{SingleCellExperiment} object with pathway activity scores from GSVA stored in \code{reducedDim} as \code{GSVA_geneSetCollectionName_Scores}.
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-
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+#' @return A \linkS4class{SingleCellExperiment} object with pathway activity 
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+#' scores from GSVA stored in \code{reducedDim} as 
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+#' \code{GSVA_geneSetCollectionName_Scores}.
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 #' @export
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-#' 
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 #' @examples
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 #' data(scExample, package = "singleCellTK")
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 #' sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")
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@@ -23,36 +25,35 @@
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 #' 
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 #' sce <- importGeneSetsFromList(inSCE = sce,geneSetList = gs,
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 #'                                            by = "rownames")
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-#' sce <- runGSVA(inSCE = sce, geneSetCollectionName = "GeneSetCollection", useAssay = "logcounts")
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-#'
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-#'  
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-
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+#' sce <- runGSVA(inSCE = sce, 
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+#'                geneSetCollectionName = "GeneSetCollection", 
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+#'                useAssay = "logcounts")
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 runGSVA <- function(inSCE, useAssay = "logcounts",
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                     resultNamePrefix = NULL, geneSetCollectionName, ...){
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-    gsvaRes <- NULL
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-    gene.Set <- .getGeneSetCollection(inSCE, geneSetCollectionName)
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+  gsvaRes <- NULL
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+  gene.Set <- .getGeneSetCollection(inSCE, geneSetCollectionName)
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+  message(date(), " ... Running GSVA")
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+  gsvaRes <- t(GSVA::gsva(as.matrix(expData(inSCE, useAssay)),
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+                          gene.Set))
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-    gsvaRes <- t(GSVA::gsva(as.matrix(expData(inSCE, useAssay)),
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-                                           gene.Set))
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-    
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-   if(is.null(resultNamePrefix)) {
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-      resultNamePrefix <- paste0("GSVA_", geneSetCollectionName, "_")
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-   }
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-    
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-   SingleCellExperiment::reducedDim(inSCE, paste0(resultNamePrefix, "Scores")) <- gsvaRes 
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-   
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-   if ("pathwayAnalysisResultNames" %in% names(S4Vectors::metadata(inSCE))) {
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-     S4Vectors::metadata(inSCE)[["pathwayAnalysisResultNames"]] <- 
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-       c(S4Vectors::metadata(inSCE)[["pathwayAnalysisResultNames"]],
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-         paste0(resultNamePrefix, "Scores"))
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-   } else {
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-     S4Vectors::metadata(inSCE)[["pathwayAnalysisResultNames"]] <- 
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-       c(paste0(resultNamePrefix, "Scores"))
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-   }
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+  if(is.null(resultNamePrefix)) {
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+    resultNamePrefix <- paste0("GSVA_", geneSetCollectionName, "_")
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+  }
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+  SingleCellExperiment::reducedDim(inSCE, 
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+                                   paste0(resultNamePrefix, 
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+                                          "Scores")) <- gsvaRes 
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+  if ("pathwayAnalysisResultNames" %in% names(S4Vectors::metadata(inSCE))) {
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+    S4Vectors::metadata(inSCE)[["pathwayAnalysisResultNames"]] <- 
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+      c(S4Vectors::metadata(inSCE)[["pathwayAnalysisResultNames"]],
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+        paste0(resultNamePrefix, "Scores"))
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+  } else {
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+    S4Vectors::metadata(inSCE)[["pathwayAnalysisResultNames"]] <- 
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+      c(paste0(resultNamePrefix, "Scores"))
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+  }
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+
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   return(inSCE)
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 }
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-
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no message

nida pervaiz authored on 29/12/2021 10:41:47
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@@ -9,7 +9,7 @@
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 #' @param resultNamePrefix  Character. Prefix to the name the GSVA results which will be stored in the reducedDim slot of \code{inSCE}. The names of the output matrix will be \code{resultNamePrefix_Scores}. If this parameter is set to \code{NULL}, then "GSVA_geneSetCollectionName_" will be used. Default \code{NULL}.
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 #' @param ... Parameters to pass to gsva()
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 #'
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-#' @return   A \link[SingleCellExperiment]{SingleCellExperiment} object with pathway activity scores from GSVA stored in \code{reducedDim} as \code{GSVA_NameOfTheGeneset_Scores}.
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+#' @return   A \link[SingleCellExperiment]{SingleCellExperiment} object with pathway activity scores from GSVA stored in \code{reducedDim} as \code{GSVA_geneSetCollectionName_Scores}.
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 #' @export
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 #' 
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edit in description

nida pervaiz authored on 29/12/2021 09:53:48 • Unais Qayyum committed on 29/12/2021 09:53:48
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@@ -6,10 +6,10 @@
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 #' @param useAssay Indicate which assay to use. The default is "logcounts"
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 #' @param geneSetCollectionName Character. The name of the gene set collection to use.
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 #' parameter.
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-#' @param resultNamePrefix  Character. Prefix to the name the VAM results which will be stored in the reducedDim slot of \code{inSCE}. The names of the output matrices will be \code{resultNamePrefix_Distance} and \code{resultNamePrefix_CDF}. If this parameter is set to \code{NULL}, then "VAM_geneSetCollectionName_" will be used. Default \code{NULL}.
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+#' @param resultNamePrefix  Character. Prefix to the name the GSVA results which will be stored in the reducedDim slot of \code{inSCE}. The names of the output matrix will be \code{resultNamePrefix_Scores}. If this parameter is set to \code{NULL}, then "GSVA_geneSetCollectionName_" will be used. Default \code{NULL}.
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 #' @param ... Parameters to pass to gsva()
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 #'
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-#' @return   A \link[SingleCellExperiment]{SingleCellExperiment} object with pathway activity scores from GSVA stored in \code{reducedDim} as \code{GSVA__NameOfTheGeneset_Scores}.
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+#' @return   A \link[SingleCellExperiment]{SingleCellExperiment} object with pathway activity scores from GSVA stored in \code{reducedDim} as \code{GSVA_NameOfTheGeneset_Scores}.
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 #' @export
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 #' 
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Add plotPathway() with helper functions; Add tutorial script in data-raw/

Yichen Wang authored on 15/12/2021 20:58:16
Showing1 changed files
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@@ -42,7 +42,15 @@ runGSVA <- function(inSCE, useAssay = "logcounts",
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    }
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    SingleCellExperiment::reducedDim(inSCE, paste0(resultNamePrefix, "Scores")) <- gsvaRes 
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-    
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+   
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+   if ("pathwayAnalysisResultNames" %in% names(S4Vectors::metadata(inSCE))) {
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+     S4Vectors::metadata(inSCE)[["pathwayAnalysisResultNames"]] <- 
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+       c(S4Vectors::metadata(inSCE)[["pathwayAnalysisResultNames"]],
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+         paste0(resultNamePrefix, "Scores"))
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+   } else {
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+     S4Vectors::metadata(inSCE)[["pathwayAnalysisResultNames"]] <- 
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+       c(paste0(resultNamePrefix, "Scores"))
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+   }
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   return(inSCE)
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rungsva function

Nida Pervaiz authored on 17/08/2021 08:46:33
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new file mode 100644
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@@ -0,0 +1,50 @@
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+.myenv <- new.env(parent = emptyenv())
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+
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+#' Run GSVA analysis on a \linkS4class{SingleCellExperiment} object
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+#'
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+#' @param inSCE Input \linkS4class{SingleCellExperiment} object.
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+#' @param useAssay Indicate which assay to use. The default is "logcounts"
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+#' @param geneSetCollectionName Character. The name of the gene set collection to use.
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+#' parameter.
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+#' @param resultNamePrefix  Character. Prefix to the name the VAM results which will be stored in the reducedDim slot of \code{inSCE}. The names of the output matrices will be \code{resultNamePrefix_Distance} and \code{resultNamePrefix_CDF}. If this parameter is set to \code{NULL}, then "VAM_geneSetCollectionName_" will be used. Default \code{NULL}.
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+#' @param ... Parameters to pass to gsva()
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+#'
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+#' @return   A \link[SingleCellExperiment]{SingleCellExperiment} object with pathway activity scores from GSVA stored in \code{reducedDim} as \code{GSVA__NameOfTheGeneset_Scores}.
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+
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+#' @export
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+#' 
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+#' @examples
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+#' data(scExample, package = "singleCellTK")
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+#' sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")
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+#' sce <- scaterlogNormCounts(sce, assayName = "logcounts")
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+#' gs1 <- rownames(sce)[seq(10)]
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+#' gs2 <- rownames(sce)[seq(11,20)]
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+#' gs <- list("geneset1" = gs1, "geneset2" = gs2)
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+#' 
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+#' sce <- importGeneSetsFromList(inSCE = sce,geneSetList = gs,
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+#'                                            by = "rownames")
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+#' sce <- runGSVA(inSCE = sce, geneSetCollectionName = "GeneSetCollection", useAssay = "logcounts")
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+#'
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+#'  
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+
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+runGSVA <- function(inSCE, useAssay = "logcounts",
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+                    resultNamePrefix = NULL, geneSetCollectionName, ...){
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+    gsvaRes <- NULL
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+    gene.Set <- .getGeneSetCollection(inSCE, geneSetCollectionName)
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+  
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+  
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+    gsvaRes <- t(GSVA::gsva(as.matrix(expData(inSCE, useAssay)),
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+                                           gene.Set))
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+  
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+    
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+   if(is.null(resultNamePrefix)) {
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+      resultNamePrefix <- paste0("GSVA_", geneSetCollectionName, "_")
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+   }
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+    
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+   SingleCellExperiment::reducedDim(inSCE, paste0(resultNamePrefix, "Scores")) <- gsvaRes 
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+    
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+  
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+  
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+  return(inSCE)
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+}
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+