Skip to contents

Load in mtx/plain text files to SingleCells

load_mtx.Rd

This is a helper function to load in mtx files and corresponding plain text files. It will automatically filter out low quality cells and only keep high quality cells. Under the hood DucKDB and high performance Rust binary files are being used to store the counts.

Usage

load_mtx(
  object,
  sc_mtx_io_param = params_sc_mtx_io(),
  sc_qc_param = params_sc_min_quality(),
  streaming = TRUE,
  batch_size = 1000L,
  .verbose = TRUE
)

Arguments

object

SingleCells class.

sc_mtx_io_param

List. Please generate this one via params_sc_mtx_io(). Needs to contain:

  • path_mtx - String. Path to the .mtx file

  • path_obs - String. Path to the file containing cell/barcode info.

  • path_var - String. String. Path to the file containing gene/variable info.

  • cells_as_rows - Boolean. Do cells represent the rows or columns.

sc_qc_param

List. Output of params_sc_min_quality(). A list with the following elements:

  • min_unique_genes - Integer. Minimum number of genes to be detected in the cell to be included.

  • min_lib_size - Integer. Minimum library size in the cell to be included.

  • min_cells - Integer. Minimum number of cells a gene needs to be detected to be included.

  • target_size - Float. Target size to normalise to. Defaults to 1e5.

streaming

Boolean. Shall the data be streamed during the conversion of CSR to CSC. Defaults to TRUE and should be used for larger data sets.

batch_size

Integer. If streaming = TRUE, how many cells to process in one batch. Defaults to 1000L.

.verbose

Boolean. Controls the verbosity of the function.

Value

It will populate the files on disk and return the class with updated shape information.