Goldilocks: A tool for identifying genomic regions that are ‘just right’

Samuel M. Nicholls, Amanda Clare, Joshua Randall

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
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Abstract

Summary: We present Goldilocks: a Python package providing functionality for collecting summary statistics, identifying shifts in variation, discovering outlier regions and locating and extracting interesting regions from one or more arbitrary genomes for further analysis, for a user-provided definition of interesting.

Availability and implementation: Goldilocks is freely available open-source software distributed under the MIT licence. Source code is hosted publicly at https://github.com/SamStudio8/goldilocks and the package may also be installed using pip install goldilocks. Documentation can be found at https://goldilocks.readthedocs.org.
Original languageEnglish
Pages (from-to)2047-2049
Number of pages3
JournalBioinformatics
Volume32
Issue number13
Early online date07 Mar 2016
DOIs
Publication statusPublished - 01 Jul 2016

Keywords

  • bioinformatics
  • genome
  • Software
  • Computational Biology/methods
  • Genomics/methods

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