| spanielPlot {Spaniel} | R Documentation |
This function overlays information from a Seurat object or SingleCellExperiment object containing barcodes onto a H & E image. There are 4 plots available showing a) the number of genes detected per spot, b) the number of reads detected per spot, c) clustering results, d) the gene expression of a selected gene.
spanielPlot(object, grob, plotType = c("NoGenes",
"CountsPerSpot",
"Cluster",
"Gene"),
gene= NULL, clusterRes = NULL, customTitle = NULL,
scaleData = TRUE, showFilter = NULL, ptSize = 2,
ptSizeMin = 0, ptSizeMax = 5)
object |
Either a Seurat object (version 3) or a SingleCellExperiment object containing barcode coordinates in the metadata (Seurat) or colData (SingleCellExperiment). |
grob |
an grob to be used as the backgound image see(parseImage) |
plotType |
There are 5 types of plots avaiable: 1) NoGenes - This shows the number of genes per spot and uses information from "nFeature_RNA" column of Seurat object or "detected" from a SingleCellExperiment object. 2) CountsPerSpot - This shows the number of counts per spot. It uses information from "nCount_RNA" column of Seurat object or "sum" from a singleCellExperiment object. 3) Cluster - This plot is designed to show clustering results stored in the meta.data or colData of an object 4) Gene- This plot shows the expression of a single gene. This plot uses scaled/normalised expressin data from the scale.data slot of Seurat object or logcounts of a SingleCellExperiment object. 5) Other - A generic plot to plot any column from the meta.data or colData of an object. |
gene |
Gene to plot |
clusterRes |
which cluster resolution to plot |
customTitle |
Specify plot title (optional) |
scaleData |
Show scaled data on plot (default is TRUE) |
showFilter |
Logical filter showing pass/fail for spots |
ptSize |
Point size used for cluster plot default is 2 |
ptSizeMin |
Minimum point size used for QC and Gene Expression plots default is 0 |
ptSizeMax |
Maximum point size used for QC and Gene Expression plots default is 5 |
A ggplot spatial transcriptomics plot
## Data is taken from DOI: 10.1126/science.aaf2403
SeuratObj <- readRDS(file.path(system.file(package = "Spaniel"),
"extdata/SeuratData.rds"))
imgFile <- readRDS(file.path(system.file(package = "Spaniel"),
"extdata/image.rds"))
## Counts per spot with a QC filter
minGenes <- 2000
minUMI <- 300000
filter <- SeuratObj$nFeature_RNA > minGenes &
SeuratObj$nCount_RNA > minUMI
spanielPlot(object = SeuratObj, grob = imgFile,
plotType = "CountsPerSpot",
showFilter = filter)
## Cluster plot
spanielPlot(object = SeuratObj, grob = imgFile,
plotType = "Cluster",
clusterRes = "cluster_RNA_snn_res.0.6")
## Gene plot
spanielPlot(object = SeuratObj, grob = imgFile,
plotType = "Gene",
gene= "Nrgn")