SquiggleKit: a toolkit for manipulating nanopore signal data

SUMMARY: The management of raw nanopore sequencing data poses a challenge that must be overcome to facilitate the creation of new bioinformatics algorithms predicated on signal analysis. SquiggleKit is a toolkit for manipulating and interrogating nanopore data that simplifies file handling, data ext...

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Detalles Bibliográficos
Autores principales: Ferguson, James M, Smith, Martin A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887521/
https://www.ncbi.nlm.nih.gov/pubmed/31332428
http://dx.doi.org/10.1093/bioinformatics/btz586
Descripción
Sumario:SUMMARY: The management of raw nanopore sequencing data poses a challenge that must be overcome to facilitate the creation of new bioinformatics algorithms predicated on signal analysis. SquiggleKit is a toolkit for manipulating and interrogating nanopore data that simplifies file handling, data extraction, visualization and signal processing. AVAILABILITY AND IMPLEMENTATION: SquiggleKit is cross platform and freely available from GitHub at (https://github.com/Psy-Fer/SquiggleKit). Detailed documentation can be found at (https://psy-fer.github.io/SquiggleKitDocs/). All tools have been designed to operate in python 2.7+, with minimal additional libraries. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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