singlecell_processor: call BISCUIT

In xieguigang/biscuit: R Codebase for BISCUIT: Infinite Mixture Model to cluster and impute single cells.

Description

run single cell data pre-processing via BISCUIT algorithm.

Usage

singlecell_processor(
  input_file_name = stop("missing the raw data table file!"),
  input_data_tab_delimited = TRUE,
  is_format_genes_cells = TRUE,
  choose_cells = 3000,
  choose_genes = 150,
  gene_batch = 50,
  num_iter = 20,
  num_cores = detectCores() - 4,
  z_true_labels_avl = TRUE,
  num_cells_batch = 1000,
  alpha = 1,
  output_folder_name = "./output"
)

Arguments

input_data_tab_delimited	set to TRUE if the input data is tab-delimited
is_format_genes_cells	set to TRUE if input data has rows as genes and columns as cells
choose_cells	comment if you want all the cells to be considered
choose_genes	comment if you want all the genes to be considered
gene_batch	number of genes per batch, therefore num_batches = choose_genes (or numgenes)/gene_batch. Max value is 150
num_iter	number of iterations, choose based on data size.
num_cores	number of cores for parallel processing. Ensure that detectCores() > 1 for parallel processing to work, else set num_cores to 1.
z_true_labels_avl	set this to TRUE if the true labels of cells are available, else set it to FALSE. If TRUE, ensure to populate 'z_true' with the true labels in 'BISCUIT_process_data.R'
num_cells_batch	set this to 1000 if input number of cells is in the 1000s, else set it to 100.
alpha	DPMM dispersion parameter. A higher value spins more clusters whereas a lower value spins lesser clusters.
output_folder_name	give a name for your output folder.

xieguigang/biscuit documentation built on Dec. 23, 2021, 6:19 p.m.