Bioframe: operations on genomic intervals in Pandas dataframes.

Autor:	Abdennur N; Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, United States.; Department of Systems Biology, UMass Chan Medical School, Worcester, MA 01605, United States., Fudenberg G; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, United States., Flyamer IM; Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland., Galitsyna AA; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, United States., Goloborodko A; Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), 1030 Vienna, Austria., Imakaev M; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, United States., Venev S; Department of Systems Biology, UMass Chan Medical School, Worcester, MA 01605, United States.
Jazyk:	angličtina
Zdroj:	Bioinformatics (Oxford, England) [Bioinformatics] 2024 Feb 01; Vol. 40 (2).
DOI:	10.1093/bioinformatics/btae088
Abstrakt:	Motivation: Genomic intervals are one of the most prevalent data structures in computational genome biology, and used to represent features ranging from genes, to DNA binding sites, to disease variants. Operations on genomic intervals provide a language for asking questions about relationships between features. While there are excellent interval arithmetic tools for the command line, they are not smoothly integrated into Python, one of the most popular general-purpose computational and visualization environments. Results: Bioframe is a library to enable flexible and performant operations on genomic interval dataframes in Python. Bioframe extends the Python data science stack to use cases for computational genome biology by building directly on top of two of the most commonly-used Python libraries, NumPy and Pandas. The bioframe API enables flexible name and column orders, and decouples operations from data formats to avoid unnecessary conversions, a common scourge for bioinformaticians. Bioframe achieves these goals while maintaining high performance and a rich set of features. Availability and Implementation: Bioframe is open-source under MIT license, cross-platform, and can be installed from the Python Package Index. The source code is maintained by Open2C on GitHub at https://github.com/open2c/bioframe. (© The Author(s) 2024. Published by Oxford University Press.)
Databáze:	MEDLINE
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