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Pairtools: From sequencing data to chromosome contacts.

null nullNezar AbdennurGeoffrey FudenbergIlya M FlyamerAleksandra A GalitsynaAnton GoloborodkoMaxim ImakaevSergey V Venev
Published in: PLoS computational biology (2024)
The field of 3D genome organization produces large amounts of sequencing data from Hi-C and a rapidly-expanding set of other chromosome conformation protocols (3C+). Massive and heterogeneous 3C+ data require high-performance and flexible processing of sequenced reads into contact pairs. To meet these challenges, we present pairtools-a flexible suite of tools for contact extraction from sequencing data. Pairtools provides modular command-line interface (CLI) tools that can be flexibly chained into data processing pipelines. The core operations provided by pairtools are parsing of.sam alignments into Hi-C pairs, sorting and removal of PCR duplicates. In addition, pairtools provides auxiliary tools for building feature-rich 3C+ pipelines, including contact pair manipulation, filtration, and quality control. Benchmarking pairtools against popular 3C+ data pipelines shows advantages of pairtools for high-performance and flexible 3C+ analysis. Finally, pairtools provides protocol-specific tools for restriction-based protocols, haplotype-resolved contacts, and single-cell Hi-C. The combination of CLI tools and tight integration with Python data analysis libraries makes pairtools a versatile foundation for a broad range of 3C+ pipelines.
Keyphrases
  • data analysis
  • single cell
  • electronic health record
  • big data
  • randomized controlled trial
  • machine learning
  • blood brain barrier
  • high throughput
  • deep learning
  • gene expression
  • genome wide