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Goldilocks: a tool for identifying genomic regions that are ‘just right’
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 defini...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4920124/ https://www.ncbi.nlm.nih.gov/pubmed/27153673 http://dx.doi.org/10.1093/bioinformatics/btw116 |
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author | Nicholls, Samuel M. Clare, Amanda Randall, Joshua C. |
author_facet | Nicholls, Samuel M. Clare, Amanda Randall, Joshua C. |
author_sort | Nicholls, Samuel M. |
collection | PubMed |
description | 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. Contact: msn@aber.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4920124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-49201242016-06-27 Goldilocks: a tool for identifying genomic regions that are ‘just right’ Nicholls, Samuel M. Clare, Amanda Randall, Joshua C. Bioinformatics Applications Notes 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. Contact: msn@aber.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2016-07-01 2016-03-07 /pmc/articles/PMC4920124/ /pubmed/27153673 http://dx.doi.org/10.1093/bioinformatics/btw116 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Nicholls, Samuel M. Clare, Amanda Randall, Joshua C. Goldilocks: a tool for identifying genomic regions that are ‘just right’ |
title | Goldilocks: a tool for identifying genomic regions that are ‘just right’ |
title_full | Goldilocks: a tool for identifying genomic regions that are ‘just right’ |
title_fullStr | Goldilocks: a tool for identifying genomic regions that are ‘just right’ |
title_full_unstemmed | Goldilocks: a tool for identifying genomic regions that are ‘just right’ |
title_short | Goldilocks: a tool for identifying genomic regions that are ‘just right’ |
title_sort | goldilocks: a tool for identifying genomic regions that are ‘just right’ |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4920124/ https://www.ncbi.nlm.nih.gov/pubmed/27153673 http://dx.doi.org/10.1093/bioinformatics/btw116 |
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