Learn R Programming

SlimR (version 1.0.7)

Celltype_Annotation_Heatmap: Uses "marker_list" to generate heatmap for cell annotation

Description

Uses "marker_list" to generate heatmap for cell annotation

Usage

Celltype_Annotation_Heatmap(
  seurat_obj,
  gene_list,
  species,
  cluster_col = "seurat_clusters",
  assay = "RNA",
  min_expression = 0.1,
  specificity_weight = 3,
  colour_low = "navy",
  colour_high = "firebrick3"
)

Value

The heatmap of the comparison between "cluster_col" in the Seurat object and the given gene set "gene_list" needs to be annotated.

Arguments

seurat_obj

Enter the Seurat object with annotation columns such as "seurat_cluster" in meta.data to be annotated.

gene_list

A list of cells and corresponding gene controls, the name of the list is cell type, and the first column of the list corresponds to markers. Lists can be generated using functions such as "Markers_filter_Cellmarker2 ()", "Markers_filter_PanglaoDB ()", "read_excel_markers ()", "read_seurat_markers ()", etc.

species

This parameter selects the species "Human" or "Mouse" for standard gene format correction of markers entered by "Marker_list".

cluster_col

Enter annotation columns such as "seurat_cluster" in meta.data of the Seurat object to be annotated. Default parameters use "cluster_col = 'seurat_clusters'".

assay

Enter the assay used by the Seurat object, such as "RNA". Default parameters use "assay = 'RNA'".

min_expression

The min_expression parameter defines a threshold value to determine whether a cell's expression of a feature is considered "expressed" or not. It is used to filter out low-expression cells that may contribute noise to the analysis. Default parameters use "min_expression = 0.1".

specificity_weight

The specificity_weight parameter controls how much the expression variability (standard deviation) of a feature within a cluster contributes to its "specificity score." It amplifies or suppresses the impact of variability in the final score calculation.Default parameters use "specificity_weight = 3".

colour_low

Color for lowest probability level in Heatmap visualization of probability matrix. (default = "navy")

colour_high

Color for highest probability level Heatmap visualization of probability matrix. (default = "firebrick3")

See Also

Other Semi_Automated_Annotation_Workflow: Celltype_Annotation_Combined(), Celltype_Annotation_Features()

Examples

Run this code
if (FALSE) {
Celltype_Annotation_Heatmap(seurat_obj = sce,
    gene_list = Markers_list,
    species = "Human",
    cluster_col = "seurat_clusters",
    assay = "RNA",
    min_expression = 0.1,
    specificity_weight = 3,
    colour_low = "navy",
    colour_high = "firebrick3"
    )
    }

Run the code above in your browser using DataLab