Cooltools: Enabling high-resolution Hi-C analysis in Python

Chromosome conformation capture (3C) technologies reveal the incredible complexity of genome organization. Maps of increasing size, depth, and resolution are now used to probe genome architecture across cell states, types, and organisms. Larger datasets add challenges at each step of computational a...

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Bibliographic Details
Published in:PLoS computational biology 2024-05, Vol.20 (5), p.e1012067-e1012067
Main Authors: Abdennur, Nezar, Abraham, Sameer, Fudenberg, Geoffrey, Flyamer, Ilya M, Galitsyna, Aleksandra A, Goloborodko, Anton, Imakaev, Maxim, Oksuz, Betul A, Venev, Sergey V, Xiao, Yao
Format: Article
Language:English
Subjects:
Analysis
Application programming interface
Biology and Life Sciences
Cell cycle
Cell division
Chromosomes
Cluster analysis
Computer applications
Conformation
Data analysis
Datasets
Ecosystems
Flexibility
Genomes
Genomics
High resolution
Line interfaces
Physical Sciences
Proteins
Python (Programming language)
Research and Analysis Methods
Software
Sparsity
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Summary:Chromosome conformation capture (3C) technologies reveal the incredible complexity of genome organization. Maps of increasing size, depth, and resolution are now used to probe genome architecture across cell states, types, and organisms. Larger datasets add challenges at each step of computational analysis, from storage and memory constraints to researchers' time; however, analysis tools that meet these increased resource demands have not kept pace. Furthermore, existing tools offer limited support for customizing analysis for specific use cases or new biology. Here we introduce cooltools (https://github.com/open2c/cooltools), a suite of computational tools that enables flexible, scalable, and reproducible analysis of high-resolution contact frequency data. Cooltools leverages the widely-adopted cooler format which handles storage and access for high-resolution datasets. Cooltools provides a paired command line interface (CLI) and Python application programming interface (API), which respectively facilitate workflows on high-performance computing clusters and in interactive analysis environments. In short, cooltools enables the effective use of the latest and largest genome folding datasets.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1012067