Get_monocle: To analyse the seurat.obj easily

In Lian-Lab/LIANLAB: To integrate analysis methods and simplify analysis process

Description

To analyse the seurat.obj easily

Usage

Get_monocle(
  seurat_object,
  gene_ann = NULL,
  n_cell = NULL,
  num_expressed = 1,
  batch_if = NULL,
  remove_batch = F,
  dispersion_empiricals = 0.1,
  mean_expressions = 0.01,
  ordering_genes = NULL
)

Arguments

seurat_object	seurat.obj
gene_ann	gene information rownames are genenames, and a col named 'gene_short_name'
n_cell	barcode of the mixed cells, default NULL
num_expressed	the lowest gene expression, default
batch_if	batch factor, default NULL
remove_batch	whether to remove the batch effect caused by the batch factor
dispersion_empiricals	dispersion empiricals
mean_expressions	mean expressions
ordering_genes	marks genes that will be used for clustering in subsequent calls to clusterCells

Value

a list, including cds and cluster DE genes

Examples

## Not run: 
input.file <- system.file('extdata','pbmc_1k.RDS',package = 'LIANLABDATA')
pbmc_1k <- readRDS(input.file)
cds.list <- Get_monocle(pbmc_1k)

## End(Not run)

Lian-Lab/LIANLAB documentation built on June 23, 2021, 5:37 a.m.