Skip to content

Python bindings for hictk: read and write .cool and .hic files directly from Python

License

Notifications You must be signed in to change notification settings

paulsengroup/hictkpy

Repository files navigation

hictkpy

License CI Download from Bioconda docs Zenodo DOI

Python bindings for hictk, a blazing fast toolkit to work with .hic and .cool files.

Installing hictkpy

hictkpy can be installed in various ways. The simples method is using pip: pip install hictkpy.

Refer to Installation for alternative methods.

Using hictkpy

import hictkpy

path_to_clr = "file.mcool"  # "file.hic"

clr = hictkpy.File(path_to_clr, 100_000)
sel = clr.fetch("chr1")

df = sel.to_df()     # Get interactions as a pd.DataFrame
m1 = sel.to_numpy()  # Get interactions as a numpy matrix
m2 = sel.to_coo()    # Get interactions as a scipy.sparse.coo_matrix

For more detailed examples refer to Quickstart.

The complete documentation for hictkpy API is available here.

Citing

If you use hictkpy in you reaserch, please cite the following publication:

Roberto Rossini, Jonas Paulsen, hictk: blazing fast toolkit to work with .hic and .cool files Bioinformatics, Volume 40, Issue 7, July 2024, btae408, https://doi.org/10.1093/bioinformatics/btae408

BibTex
@article{hictk,
    author = {Rossini, Roberto and Paulsen, Jonas},
    title = "{hictk: blazing fast toolkit to work with .hic and .cool files}",
    journal = {Bioinformatics},
    volume = {40},
    number = {7},
    pages = {btae408},
    year = {2024},
    month = {06},
    issn = {1367-4811},
    doi = {10.1093/bioinformatics/btae408},
    url = {https://doi.org/10.1093/bioinformatics/btae408},
    eprint = {https://academic.oup.com/bioinformatics/article-pdf/40/7/btae408/58385157/btae408.pdf},
}