analysis/start_file.R

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

## 21st Dec 2016
## BISCUIT R implementation
## Start_file with user inputs
## 
## Code author SP

require(biscuit);

biscuit::singlecell_processor(
    input_file_name          = "./expression_mRNA_17-Aug-2014.txt",
    input_data_tab_delimited = TRUE, # set to TRUE if the input data is tab-delimited
    is_format_genes_cells    = TRUE, # set to TRUE if input data has rows as genes and columns as cells
    choose_cells             = 3000, # comment if you want all the cells to be considered
    choose_genes             = 150,  # comment if you want all the genes to be considered
    gene_batch               = 50,   # number of genes per batch, therefore num_batches = choose_genes (or numgenes)/gene_batch. Max value is 150
    num_iter                 = 20,   # number of iterations, choose based on data size.
    num_cores                = detectCores() - 4, # 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        = TRUE, # 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          = 1000, # set this to 1000 if input number of cells is in the 1000s, else set it to 100.
    alpha                    = 1,    # DPMM dispersion parameter. A higher value spins more clusters whereas a lower 
                                     # value spins lesser clusters.

    # give a name for your output folder.
    output_folder_name = "./output" 
);