CAMML {CAMML} R Documentation

## Cell-typing using variance Adjusted Mahalanobis distances with Multi-Labeling (CAMML)

### Description

Multi-label cell-typing method for single-cell RNA-sequencing data. CAMML takes in cell type-specific gene sets, with weights for each gene, and builds weighted Variance-Adjusted Mahalanobis (VAM) scores for each of them. CAMML then outputs a Seurat Object with an assay for CAMML that has the weighted VAM score for each cell type in each cell. CAMML takes in several arguments: seurat: a Seurat Object of the scRNA-seq data, gene.set.df: a data frame with a row for each gene and the following required columns: "ensemb.id" and "cell.type" and optional columns of "gene.weight" and "gene.symbol".

### Usage

    CAMML(seurat, gene.set.df)


### Arguments

 seurat A Seurat Object that has previously been normalized and scaled. gene.set.df A list of lists of genes in each gene set, with each gene set list named for the cell type it represents.

### Value

A SeuratObject with a CAMML assay with the scores for each cell type in each cell. This will be in the form of a matrix with columns for each cell and rows for each cell type that was scored.

vamForSeurat

### Examples

# Only run example code if Seurat package is available
if (requireNamespace("Seurat", quietly=TRUE) & requireNamespace("SeuratObject", quietly=TRUE)) {
# See vignettes for more examples
seurat <- CAMML(seurat=SeuratObject::pbmc_small,
gene.set.df = data.frame(cbind(ensembl.id = c("ENSG00000172005",
"ENSG00000173114","ENSG00000139187"),
cell.type = c("T cell","T cell","T cell"))))
seurat@assays\$CAMML@data
}


[Package CAMML version 0.2.2 Index]