snapatac2.pp.import_data#

snapatac2.pp.import_data(fragment_file, *, file=None, genome=None, gene_anno=None, chrom_size=None, min_num_fragments=200, min_tsse=1, sorted_by_barcode=True, low_memory=True, whitelist=None, shift_left=0, shift_right=0, chunk_size=2000, tempdir=None, backend='hdf5')[source]#

Import dataset and compute QC metrics.

This function will store fragments as base-resolution TN5 insertions in the resulting h5ad file (in .obsm['insertion']), along with the chromosome sizes (in .uns['reference_sequences']). Various QC metrics, including TSSe, number of unique fragments, duplication rate, fraction of mitochondrial DNA reads, will be computed.

Parameters:

  • fragment_file (Path) – File name of the fragment file.

  • file (Optional[Path]) – File name of the output h5ad file used to store the result. If provided, result will be saved to a backed AnnData, otherwise an in-memory AnnData is used.

  • genome (Optional[Genome]) – A Genome object, providing gene annotation and chromosome sizes. If not set, gff_file and chrom_size must be provided. genome has lower priority than gff_file and chrom_size.

  • gene_anno (Optional[Path]) – File name of the gene annotation file in GFF or GTF format. This is required if genome is not set. Setting gene_anno will override the annotations from the genome parameter.

  • chrom_size (Optional[dict[str, int]]) – A dictionary containing chromosome sizes, for example, {"chr1": 2393, "chr2": 2344, ...}. This is required if genome is not set. Setting chrom_size will override the chrom_size from the genome parameter.

  • min_num_fragments (int) – Number of unique fragments threshold used to filter cells

  • min_tsse (float) – TSS enrichment threshold used to filter cells

  • sorted_by_barcode (bool) – Whether the fragment file has been sorted by cell barcodes. If sorted_by_barcode == True, this function makes use of small fixed amout of memory. If sorted_by_barcode == False and low_memory == False, all data will be kept in memory. See low_memory for more details.

  • low_memory (bool) – Whether to use the low memory mode when sorted_by_barcode == False. It does this by first sort the records by barcodes and then process them in batch. The parameter has no effect when sorted_by_barcode == True.

  • whitelist (Union[Path, list[str], None]) – File name or a list of barcodes. If it is a file name, each line must contain a valid barcode. When provided, only barcodes in the whitelist will be retained.

  • shift_left (int) – Insertion site correction for the left end.

  • shift_right (int) – Insertion site correction for the right end. Note this has no effect on single-end reads. For single-end reads, shift_right will be set using the value of shift_left.

  • chunk_size (int) – Increasing the chunk_size speeds up I/O but uses more memory.

  • tempdir (Optional[Path]) – Location to store temporary files. If None, system temporary directory will be used.

  • backend (Literal['hdf5']) – The backend.

Returns:

An annotated data matrix of shape n_obs x n_vars. Rows correspond to cells and columns to regions. If file=None, an in-memory AnnData will be returned, otherwise a backed AnnData is returned.

Return type:

AnnData | ad.AnnData

Examples

>>> import snapatac2 as snap
>>> data = snap.pp.import_data(snap.datasets.pbmc500(), genome=snap.genome.hg38, sorted_by_barcode=False)
>>> print(data)