Generates reference gene expression data from a Seurat object by identifying marker genes for each cell type and aggregating expression data.
Usage
generateRef_seurat(
sce,
celltype = NULL,
proportion = NULL,
assay_deg = "RNA",
slot_deg = "data",
adjust_assay = FALSE,
assay_out = "RNA",
slot_out = "data",
verbose = FALSE,
only.pos = TRUE,
n_ref_genes = 50,
logfc.threshold = 0.15,
test.use = "wilcox"
)Arguments
- sce
Seurat object containing single-cell RNA-seq data.
- celltype
Character. Cell type column name in metadata. Default is `NULL` (uses default identity).
- proportion
Numeric. Proportion of cells to randomly select for analysis. Default is `NULL` (use all cells).
- assay_deg
Character. Assay for finding markers. Default is `"RNA"`.
- slot_deg
Character. Slot for finding markers. Default is `"data"`.
- adjust_assay
Logical. Whether to adjust assay for SCT. Default is `FALSE`.
- assay_out
Character. Assay for output. Default is `"RNA"`.
- slot_out
Character. Slot for output. Default is `"data"`.
- verbose
Logical. Print verbose messages. Default is `FALSE`.
- only.pos
Logical. Return only positive markers. Default is `TRUE`.
- n_ref_genes
Integer. Number of reference genes per cell type. Default is 50.
- logfc.threshold
Numeric. Log fold change threshold. Default is 0.15.
- test.use
Character. Statistical test for marker identification. Default is `"wilcox"`.
Examples
if (FALSE) { # \dontrun{
if (requireNamespace("Seurat", quietly = TRUE)) {
pbmc <- SeuratObject::pbmc_small
sm <- generateRef_seurat(sce = pbmc, celltype = "groups", slot_out = "data")
}
} # }