npervaiz authored on 02/01/2023 19:12:26
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@@ -69,10 +69,10 @@ plotScanpyMarkerGenesMatrixPlot |
| 69 | 69 |
data(scExample, package = "singleCellTK") |
| 70 | 70 |
\dontrun{
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| 71 | 71 |
sce <- runScanpyNormalizeData(sce, useAssay = "counts") |
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+sce <- runScanpyFindHVG(sce, useAssay = "scanpyNormData", method = "seurat") |
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| 72 | 73 |
sce <- runScanpyScaleData(sce, useAssay = "scanpyNormData") |
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-sce <- runScanpyFindHVG(sce, useAssay = "scanpyScaledData", method = "seurat") |
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-sce <- runScanpyPCA(sce, useAssay = "scanpyNormData") |
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-sce <- runScanpyFindClusters(sce, useAssay = "counts") |
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+sce <- runScanpyPCA(sce, useAssay = "scanpyScaledData") |
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+sce <- runScanpyFindClusters(sce, useReducedDim = "scanpyPCA") |
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| 76 | 76 |
sce <- runScanpyFindMarkers(sce, colDataName = "Scanpy_louvain_1" ) |
| 77 | 77 |
plotScanpyMarkerGenesMatrixPlot(sce, groupBy = 'Scanpy_louvain_1') |
| 78 | 78 |
} |
npervaiz authored on 22/12/2022 12:16:44
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@@ -69,6 +69,8 @@ plotScanpyMarkerGenesMatrixPlot |
| 69 | 69 |
data(scExample, package = "singleCellTK") |
| 70 | 70 |
\dontrun{
|
| 71 | 71 |
sce <- runScanpyNormalizeData(sce, useAssay = "counts") |
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+sce <- runScanpyScaleData(sce, useAssay = "scanpyNormData") |
|
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+sce <- runScanpyFindHVG(sce, useAssay = "scanpyScaledData", method = "seurat") |
|
| 72 | 74 |
sce <- runScanpyPCA(sce, useAssay = "scanpyNormData") |
| 73 | 75 |
sce <- runScanpyFindClusters(sce, useAssay = "counts") |
| 74 | 76 |
sce <- runScanpyFindMarkers(sce, colDataName = "Scanpy_louvain_1" ) |
npervaiz authored on 02/11/2022 12:13:26
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@@ -71,7 +71,7 @@ data(scExample, package = "singleCellTK") |
| 71 | 71 |
sce <- runScanpyNormalizeData(sce, useAssay = "counts") |
| 72 | 72 |
sce <- runScanpyPCA(sce, useAssay = "scanpyNormData") |
| 73 | 73 |
sce <- runScanpyFindClusters(sce, useAssay = "counts") |
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-sce <- runScanpyFindMarkers(sce, colDataName = "Scanpy_louvain" ) |
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-plotScanpyMarkerGenesMatrixPlot(sce, groupBy = 'Scanpy_louvain') |
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+sce <- runScanpyFindMarkers(sce, colDataName = "Scanpy_louvain_1" ) |
|
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+plotScanpyMarkerGenesMatrixPlot(sce, groupBy = 'Scanpy_louvain_1') |
|
| 76 | 76 |
} |
| 77 | 77 |
} |
npervaiz authored on 12/10/2022 14:09:33
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new file mode 100644 |
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@@ -0,0 +1,77 @@ |
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+% Generated by roxygen2: do not edit by hand |
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+% Please edit documentation in R/scanpyFunctions.R |
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+\name{plotScanpyMarkerGenesMatrixPlot}
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+\alias{plotScanpyMarkerGenesMatrixPlot}
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+\title{plotScanpyMarkerGenesMatrixPlot}
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+\usage{
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+plotScanpyMarkerGenesMatrixPlot( |
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+ inSCE, |
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+ groups = NULL, |
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+ nGenes = 10, |
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+ groupBy, |
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+ log2fcThreshold = NULL, |
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+ parameters = "logfoldchanges", |
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+ standardScale = "var", |
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+ features = NULL, |
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+ title = "", |
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+ vmin = NULL, |
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+ vmax = NULL, |
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+ colorBarTitle = "log fold change" |
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+) |
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+} |
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+\arguments{
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+\item{inSCE}{Input \code{SingleCellExperiment} object.}
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+ |
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+\item{groups}{The groups for which to show the gene ranking. Default \code{NULL}
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+means that all groups will be considered.} |
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+ |
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+\item{nGenes}{Number of genes to show. Default \code{10}}
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+ |
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+\item{groupBy}{The key of the observation grouping to consider. By default,
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+the groupby is chosen from the rank genes groups parameter.} |
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+ |
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+\item{log2fcThreshold}{Only output DEGs with the absolute values of log2FC
|
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+larger than this value. Default \code{NULL}.}
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+ |
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+\item{parameters}{The options for marker genes results to plot are:
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+‘scores’, ‘logfoldchanges’, ‘pvals’, ‘pvals_adj’, ‘log10_pvals’, ‘log10_pvals_adj’. |
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+If NULL provided then it uses mean gene value to plot.} |
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+ |
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+\item{standardScale}{Whether or not to standardize the given dimension
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+between 0 and 1, meaning for each variable or group, subtract the minimum and |
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+divide each by its maximum. Default \code{NULL} means that it doesn't perform
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+any scaling.} |
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+ |
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+\item{features}{Genes to plot. Sometimes is useful to pass a specific list of
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+var names (e.g. genes) to check their fold changes or p-values, instead of |
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+the top/bottom genes. The var_names could be a dictionary or a list. |
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+Default \code{NULL}}
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+ |
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+\item{title}{Provide title for the figure.}
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+ |
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+\item{vmin}{The value representing the lower limit of the color scale.
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+Values smaller than vmin are plotted with the same color as vmin. |
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+Default \code{NULL}}
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+ |
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+\item{vmax}{The value representing the upper limit of the color scale.
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+Values larger than vmax are plotted with the same color as vmax. |
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+Default \code{NULL}}
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+ |
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+\item{colorBarTitle}{Title for the color bar.}
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+} |
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+\value{
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+plot object |
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+} |
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+\description{
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+plotScanpyMarkerGenesMatrixPlot |
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+} |
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+\examples{
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+data(scExample, package = "singleCellTK") |
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+\dontrun{
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+sce <- runScanpyNormalizeData(sce, useAssay = "counts") |
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+sce <- runScanpyPCA(sce, useAssay = "scanpyNormData") |
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+sce <- runScanpyFindClusters(sce, useAssay = "counts") |
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+sce <- runScanpyFindMarkers(sce, colDataName = "Scanpy_louvain" ) |
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+plotScanpyMarkerGenesMatrixPlot(sce, groupBy = 'Scanpy_louvain') |
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+} |
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+} |