anndata_to_ctd: Convert: 'AnnData' ==> 'CellTypeDataset'

In bschilder/scKirby: Automated ingestion and conversion of various single-cell data formats.

Convert: AnnData ==> CellTypeDataset

Description

Convert: AnnData ==> CellTypeDataset

Usage

anndata_to_ctd(
  obj,
  annotLevels,
  dataset = basename(tempfile()),
  chunk_size = NULL,
  agg_fun = "mean",
  agg_method = c("monocle3", "stats"),
  dropNA = TRUE,
  standardise = TRUE,
  as_sparse = TRUE,
  as_delayedarray = FALSE,
  verbose = TRUE,
  ...
)

Arguments

obj	A single-cell object supported by scKirby. See converters for a table of all supported conversions.
annotLevels	List with arrays of strings containing the cell type names associated with each column in exp.
dataset	CellTypeData. name.
chunk_size	An integer indicating number of cells to include per chunk. This can be a more memory efficient and scalable way of aggregating on-disk data formats like AnnData, rather than reading in the entire matrix into memory at once (default: NULL).
agg_fun	Aggregation function passed to aggregate_mapped_genes. Set to NULL to skip aggregation step (default).
agg_method	Aggregation method.
dropNA	Drop genes assigned to NA in groupings.
standardise	Run standardise_ctd.
as_sparse	Convert gene_df to a sparse matrix. Only works if gene_df is one of the following classes: matrix Matrix data.frame data.table tibble If gene_df is a sparse matrix to begin with, it will be returned as a sparse matrix (so long as gene_output= "rownames" or "colnames").
as_delayedarray	Convert aggregated matrix to DelayedArray.
verbose	Print messages.
...	Arguments passed on to EWCE::standardise_ctd ctd Input CellTypeData. input_species Which species the gene names in exp come from. See list_species for all available species. output_species Which species' genes names to convert exp to. See list_species for all available species. sctSpecies_origin Species that the sct_data originally came from, regardless of its current gene format (e.g. it was previously converted from mouse to human gene orthologs). This is used for computing an appropriate backgrund. non121_strategy How to handle genes that don't have 1:1 mappings between input_species:output_species. Options include: "drop_both_species" or "dbs" or 1 : Drop genes that have duplicate mappings in either the input_species or output_species (DEFAULT). "drop_input_species" or "dis" or 2 : Only drop genes that have duplicate mappings in the input_species. "drop_output_species" or "dos" or 3 : Only drop genes that have duplicate mappings in the output_species. "keep_both_species" or "kbs" or 4 : Keep all genes regardless of whether they have duplicate mappings in either species. "keep_popular" or "kp" or 5 : Return only the most "popular" interspecies ortholog mappings. This procedure tends to yield a greater number of returned genes but at the cost of many of them not being true biological 1:1 orthologs. "sum","mean","median","min" or "max" : When gene_df is a matrix and gene_output="rownames", these options will aggregate many-to-one gene mappings (input_species-to-output_species) after dropping any duplicate genes in the output_species. method R package to use for gene mapping: "gprofiler" : Slower but more species and genes. "homologene" : Faster but fewer species and genes. "babelgene" : Faster but fewer species and genes. Also gives consensus scores for each gene mapping based on a several different data sources. force_new_quantiles By default, quantile computation is skipped if they have already been computed. Set =TRUE to override this and generate new quantiles. force_standardise If ctd has already been standardised, whether to rerun standardisation anyway (Default: FALSE). remove_unlabeled_clusters Remove any samples that have numeric column names. numberOfBins Number of non-zero quantile bins. keep_annot Keep the column annotation data if provided. keep_plots Keep the dendrograms if provided. as_DelayedArray Convert to DelayedArray. rename_columns Remove replace_chars from column names. make_columns_unique Rename each columns with the prefix dataset.species.celltype.

Examples

obj <- example_obj("anndata")
obj2 <- anndata_to_ctd(obj, annotLevels=list(groups=NULL))

bschilder/scKirby documentation built on Oct. 2, 2024, 10:16 p.m.