Yichen Wang authored on 14/06/2022 17:30:54 | ... | ... |
@@ -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'") |
| ... | ... |
@@ -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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| 34 | 35 |
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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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- |
nida pervaiz authored on 29/12/2021 10:41:47 | ... | ... |
@@ -9,7 +9,7 @@ |
| 9 | 9 |
#' @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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| 13 | 13 |
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#' @export |
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#' |
nida pervaiz authored on 29/12/2021 09:53:48 • Unais Qayyum committed on 29/12/2021 09:53:48 | ... | ... |
@@ -6,10 +6,10 @@ |
| 6 | 6 |
#' @param useAssay Indicate which assay to use. The default is "logcounts" |
| 7 | 7 |
#' @param geneSetCollectionName Character. The name of the gene set collection to use. |
| 8 | 8 |
#' 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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#' |
Yichen Wang authored on 15/12/2021 20:58:16 | ... | ... |
@@ -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) |
Nida Pervaiz authored on 17/08/2021 08:46:33 | 1 | 1 |
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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+ |