cell2net.preprocessing.fragment_to_bigwig#

cell2net.preprocessing.fragment_to_bigwig(fragment_file, chrom_sizes, bw_filename, normalize=True, scaling_factor=1.0, cut_sites=False, extend_cut_sites=0, cell_barcodes=None)#

Convert fragment file to BigWig format.

This function reads a fragment file, calculates coverage or cut-site signal, and writes the resulting data to a BigWig file.

Parameters:

  • fragment_file (str) – Path to the input fragment file. The file can be plain text or gzip-compressed (“.gz”).

  • chrom_sizes (dict[str, int]) – A dictionary of chromosome sizes, e.g., {“chr1”: 248956422, “chr2”: 242193529, …}.

  • bw_filename (str) – Path to the output BigWig file.

  • normalize (bool (default: True)) – If True, normalize coverage or signal values. Default is True.

  • scaling_factor (float, optional) – Factor to scale signal values if normalize is True. Default is 1.0.

  • cut_sites (bool (default: False)) – If True, compute the cut-site signal instead of coverage. Default is False.

  • extend_cut_sites (int (default: 0)) – If set cut_sites, expand cut sites for both upstream and downstream, by default: 0

Return type:

None

Returns:

Write output to bigwig file

Notes

  • The input fragment file should be tab-delimited and follow the format: Chromosome, Start, End, Barcode, Count.

  • Lines starting with # or empty lines are skipped during parsing.

  • Uses pyBigWig for writing BigWig files and polars for efficient data manipulation.

Example

>>> fragment_file = "example_fragments.tsv.gz"
>>> chrom_sizes = {"chr1": 248956422, "chr2": 242193529}
>>> bw_filename = "output.bw"
>>> fragment_to_bigwig(fragment_file, chrom_sizes, bw_filename, normalize=True, scaling_factor=1.0, cut_sites=False)