Import CellTypeDataset (CTD) references from a remote repository, standardize each, and then merge into one CTD.
merge_ctd( CTD_list, save_dir = tempdir(), standardise_CTD = FALSE, as_SCE = FALSE, gene_union = TRUE, merge_levels = seq(1, 5), save_split_SCE = FALSE, save_split_CTD = FALSE, save_merged_SCE = TRUE, force_new_quantiles = FALSE, numberOfBins = 40, as_sparse = TRUE, as_DelayedArray = FALSE, verbose = TRUE, ... )
CTD_list | (Named) list of |
---|---|
save_dir | The directory to save merged files in. |
standardise_CTD | Whether to run |
as_SCE | If |
gene_union | Whether to take the gene union or intersection when merging matrices (mean_exp,specificity, etc.). |
merge_levels | Which CTD levels you want to merge.
Can be a single value (e.g. |
save_split_SCE | Whether to save individual SCE files in the subdirectory standardized_CTD_SCE. |
save_split_CTD | Whether to save individual CTD files in the subdirectory standardized_CTD. |
save_merged_SCE | Save the final merged SCE object, or simply to return it. |
force_new_quantiles | If specificity quantiles matrix already exists, create new one. |
numberOfBins | Number of bins to compute specificity quantiles with. |
as_sparse | Convert matrices to sparse matrix. |
as_DelayedArray | Convert matrices to |
verbose | Print messages. |
... | Additional arguments to be passed to |
List of CellTypeDatasets or SingleCellExperiments.
Optionally, can return these as a merged SingleCellExperiment
.
#>#>ctd2 <- ctd1 CTD_list <- list(ctd1, ctd2) SCE_merged <- EWCE::merge_ctd( CTD_list = CTD_list, as_SCE = TRUE, gene_union = TRUE )#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#>#> [1] "ctd1" #> [1] "15259 x 7" #> [1] "ctd2" #> [1] "15259 x 7"#>#>#> [1] "ctd1" #> [1] "15259 x 48" #> [1] "ctd2" #> [1] "15259 x 48"#>#> [1] "level_1" #> [1] "level_2"#>