create_sce_by_dir {scPipe} | R Documentation |
after we run sc_gene_counting
and finish the preprocessing step. create_sce_by_dir
can be used to generate the SingleCellExperiment obeject from the folder that contains gene count matrix and QC statistics.
it can also generate the html report based on the gene count and quality control statistics
create_sce_by_dir(datadir, organism = NULL, gene_id_type = NULL, pheno_data = NULL, report = FALSE)
datadir |
the directory that contains all the data and 'stat' subfolder. |
organism |
the organism of the data. List of possible names can be retrieved using the function 'listDatasets'from 'biomaRt' package. (i.e 'mmusculus_gene_ensembl' or 'hsapiens_gene_ensembl') |
gene_id_type |
gene id type of the data A possible list of ids can be retrieved using the function 'listAttributes' from 'biomaRt' package. the commonly used id types are 'external_gene_name', 'ensembl_gene_id' or 'entrezgene' |
pheno_data |
the external phenotype data that linked to each single cell. This should be an |
report |
whether to generate the html report in the data folder |
after we run sc_gene_counting
and finish the preprocessing step. create_sce_by_dir
can be used to generate the SingleCellExperiment obeject from the folder that contains gene count matrix and QC statistics.
a SingleCellExperiment object
## Not run: # the sce can be created fron the output folder of scPipe # please refer to the vignettes sce = create_sce_by_dir(datadir="output_dir_of_scPipe", organism="mmusculus_gene_ensembl", gene_id_type="ensembl_gene_id") ## End(Not run) # or directly from the gene count and quality control matrix: data("sc_sample_data") data("sc_sample_qc") sce = SingleCellExperiment(assays = list(counts = as.matrix(sc_sample_data))) organism(sce) = "mmusculus_gene_ensembl" gene_id_type(sce) = "ensembl_gene_id" QC_metrics(sce) = sc_sample_qc demultiplex_info(sce) = cell_barcode_matching UMI_dup_info(sce) = UMI_duplication dim(sce)