paulsengroup / hictkpy

Python bindings for hictk: read and write .cool and .hic files directly from Python
MIT License
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bindings bioinformatics cooler hi-c hic hictk python3

hictkpy

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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 simplest method is using pip: pip install hictkpy[all].

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 research, 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 ```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}, } ```