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Create odm object from Cell Ranger

Source: R/import_from_cellranger.R
create_odm_from_cellranger.Rd

create_odm_from_cellranger() initializes an odm object, taking as input the output of one or more calls to Cell Ranger count. The number of odm objects returned corresponds to the number of modalities in the input data. Additionally, the cell-wise covariate data frame is computed and returned. create_odm_from_cellranger() supports the Cell Ranger modalities "Gene Expression", "CRISPR Guide Capture", and "Antibody Capture".

Usage

create_odm_from_cellranger(
  directories_to_load,
  directory_to_write,
  write_cellwise_covariates = TRUE,
  chunk_size = 1000L,
  compression_level = 3L,
  grna_target_data_frame = NULL
)

Arguments

directories_to_load

a character vector specifying the locations of the directories to load. Each directory should contain the files "matrix.mtx.gz" and "features.tsv.gz" (and optionally "barcodes.tsv.gz", which is ignored).

directory_to_write

a string indicating the directory in which to write the backing .odm files.

write_cellwise_covariates

(optional; default TRUE) a logical value indicating whether to write the cellwise covariate data frame to disk (TRUE) in addition to returning it from create_odm_from_cellranger().

chunk_size

(optional; default 1000L) a positive integer specifying the chunk size to use to store the data in the backing HDF5 file.

compression_level

(optional; default 3L) an integer in the inveral [0, 9] specifying the compression level to use to store the data in the backing HDF5 file.

grna_target_data_frame

(optional) a data frame mapping each gRNA ID to its target. Relevant only if the CRISPR modality is present within the data. (See note.)

Value

a list containing the odm object(s) and cellwise covariates.

Note

The grna_target_data_frame is relevant only for CRISPR screen data (i.e., data for which the "CRISPR Guide Capture" modality is present). In single-cell CRISPR screens, gRNAs are delivered to cells via a viral vector. Some recent single-cell CRISPR screens involve a special design in which each viral vector harbors multiple gRNAs. For example, Replogle 2022 conducted a screen in which each viral vector contained two gRNAs, each targeting the same site. In such screens, users may wish to "collapse" the gRNA count matrix by summing over the UMI counts of gRNAs contained on the same vector. To do so, users can pass the argument grna_target_data_frame, which is a data frame containing two columns: grna_id and vector_id. grna_id should coincide with the gRNA IDs as contained within the features.tsv file, and vector_id should be a string indicating the vector to which a given gRNA ID belongs. The expression vectors of gRNAs contained within the same vector are summed.

The arguments chunk_size and compression_level control the extent to which the backing .odm files are compressed, with higher values corresponding to smaller file sizes (albeit possibly longer read and write times).

Examples

library(sceptredata)
directories_to_load <- paste0(
 system.file("extdata", package = "sceptredata"),
 "/highmoi_example/gem_group_", c(1, 2)
)
directory_to_write <- tempdir()
out_list <- create_odm_from_cellranger(
  directories_to_load = directories_to_load,
  directory_to_write = directory_to_write,
)
#> Round 1/2 processing of the input files.
#> 	Processing file 1 of 2.
#> 	Processing file 2 of 2.
#> Round 2/2 processing of the input files.
#> 	Processing file 1 of 2. Computing cellwise covariates. Writing to disk.
#> 	Processing file 2 of 2. Computing cellwise covariates. Writing to disk.