Read_seurat_markers: Create "Marker_list" from Seurat object

In SlimR: Machine Learning-Assisted, Marker-Based Tool for Single-Cell and Spatial Transcriptomics Annotation

Create "Marker_list" from Seurat object

Description

Create "Marker_list" from Seurat object

Usage

Read_seurat_markers(
  df,
  sources = c("Seurat", "presto"),
  sort_by = "FSS",
  gene_filter = 20
)

Arguments

df	Dataframe generated by "FindAllMarkers" function, recommend to use parameter "group.by = "Cell_type"" and "only.pos = TRUE".
sources	Type of markers sources to use. Be one of: "Seurat" or "presto".
sort_by	Marker sorting parameter, for Seurat sources, select "avg_log2FC" or "p_val_adj" or "FSS" (Feature Significance Score, FSS, product value of log2FC and ⁠Expression ratio⁠). Default parameters use "sort_by = 'FSS'".for presto sources, select "logFC" or "padj" or "FSS". Default parameters use "sort_by = 'FSS'".
gene_filter	The number of markers left for each cell type based on the "sort_by" parameter's level of difference. Default parameters use "gene_fliter = 20"

Value

The standardized "Marker_list" in the SlimR package.

See Also

Other Section_2_Standardized_Markers_List: Markers_filter_Cellmarker2(), Markers_filter_PanglaoDB(), Read_excel_markers()

Examples

## Not run: 
# Example for Seurat sources markers
seurat_markers <- Seurat::FindAllMarkers(
    object = sce,
    group.by = "Cell_type",
    only.pos = TRUE)

Markers_list_Seurat <- Read_seurat_markers(seurat_markers,
    sources = "Seurat",
    sort_by = "avg_log2FC",
    gene_filter = 20
    )

# Example for presto sources markers
seurat_markers <- dplyr::filter(
    presto::wilcoxauc(
      X = sce,
      group_by = "Cell_type",
      seurat_assay = "RNA"
      ),
    padj < 0.05, logFC > 0.5
    )

Markers_list_Seurat <- Read_seurat_markers(seurat_markers,
    sources = "presto",
    sort_by = "logFC",
    gene_filter = 20
    )

## End(Not run)

SlimR documentation built on Dec. 17, 2025, 5:09 p.m.