## ----eval=FALSE--------------------------------------------------------------- # BiocManager::install("Rhdf5lib", type = "source") # Rhdf5lib # install.packages("ondisc") # ondisc ## ----------------------------------------------------------------------------- library(ondisc) ## ----------------------------------------------------------------------------- directories_to_load <- paste0( system.file("extdata", "highmoi_example", package = "ondisc"), "/gem_group_", 1:2 ) directories_to_load # file paths to the example data on your computer ## ----------------------------------------------------------------------------- list.files(directories_to_load[1]) ## ----------------------------------------------------------------------------- list.files(directories_to_load[2]) ## ----results="hide"----------------------------------------------------------- temp_dir <- tempdir() out_list <- create_odm_from_cellranger( directories_to_load = directories_to_load, directory_to_write = temp_dir ) ## ----------------------------------------------------------------------------- list.files(temp_dir, pattern = "*.odm") ## ----------------------------------------------------------------------------- gene_odm <- out_list[["gene"]] ## ----------------------------------------------------------------------------- gene_odm ## ----------------------------------------------------------------------------- n_features <- nrow(gene_odm) n_features n_cells <- ncol(gene_odm) n_cells ## ----------------------------------------------------------------------------- feature_ids <- rownames(gene_odm) head(feature_ids) ## ----------------------------------------------------------------------------- expression_vector <- gene_odm[2,] head(expression_vector) expression_vector <- gene_odm[rownames(gene_odm)[2],] head(expression_vector) ## ----------------------------------------------------------------------------- object.size(gene_odm) |> format(units = "Kb") ## ----------------------------------------------------------------------------- set.seed(4) example_data <- write_example_cellranger_dataset( n_features = c(100, 20, 10), n_cells = 500, n_batch = 3, modalities = c("gene", "grna", "protein"), directory_to_write = temp_dir , p_set_col_zero = 0 ) ## ----------------------------------------------------------------------------- directories_to_load <- list.files( temp_dir, pattern = "batch_", full.names = TRUE ) directories_to_load ## ----------------------------------------------------------------------------- list.files(directories_to_load[1]) ## ----results="hide"----------------------------------------------------------- out_list <- create_odm_from_cellranger( directories_to_load = directories_to_load, directory_to_write = temp_dir ) ## ----------------------------------------------------------------------------- names(out_list) ## ----------------------------------------------------------------------------- list.files(temp_dir, pattern = "*.odm") ## ----------------------------------------------------------------------------- cellwise_covariates <- out_list[["cellwise_covariates"]] head(cellwise_covariates) ## ----------------------------------------------------------------------------- temp_dir <- tempdir() gene_odm <- initialize_odm_from_backing_file( paste0(temp_dir, "/gene.odm") ) gene_odm ## ----------------------------------------------------------------------------- set.seed(4) x <- rpois(100, lambda = 1) gene_mat <- matrix( x, nrow = 5L, dimnames = list(paste0("gene_", seq_len(5L)), paste0("cell_", seq_len(20L))) ) ## ----------------------------------------------------------------------------- file_to_write <- paste0(temp_dir, "/gene.odm") gene_odm <- create_odm_from_r_matrix( mat = gene_mat, file_to_write = file_to_write, chunk_size = 5L ) ## ----------------------------------------------------------------------------- gene_odm ## ----------------------------------------------------------------------------- library(sessioninfo); session_info()