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Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data
BACKGROUND: Genomic interaction studies use next-generation sequencing (NGS) to examine the interactions between two loci on the genome, with subsequent bioinformatics analyses typically including annotation, intersection, and merging of data from multiple experiments. While many file types and anal...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5384132/ https://www.ncbi.nlm.nih.gov/pubmed/28388874 http://dx.doi.org/10.1186/s12859-017-1621-0 |
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author | Greenwald, William W. Li, He Smith, Erin N. Benaglio, Paola Nariai, Naoki Frazer, Kelly A. |
author_facet | Greenwald, William W. Li, He Smith, Erin N. Benaglio, Paola Nariai, Naoki Frazer, Kelly A. |
author_sort | Greenwald, William W. |
collection | PubMed |
description | BACKGROUND: Genomic interaction studies use next-generation sequencing (NGS) to examine the interactions between two loci on the genome, with subsequent bioinformatics analyses typically including annotation, intersection, and merging of data from multiple experiments. While many file types and analysis tools exist for storing and manipulating single locus NGS data, there is currently no file standard or analysis tool suite for manipulating and storing paired-genomic-loci: the data type resulting from “genomic interaction” studies. As genomic interaction sequencing data are becoming prevalent, a standard file format and tools for working with these data conveniently and efficiently are needed. RESULTS: This article details a file standard and novel software tool suite for working with paired-genomic-loci data. We present the paired-genomic-loci (PGL) file standard for genomic-interactions data, and the accompanying analysis tool suite “pgltools”: a cross platform, pypy compatible python package available both as an easy-to-use UNIX package, and as a python module, for integration into pipelines of paired-genomic-loci analyses. CONCLUSIONS: Pgltools is a freely available, open source tool suite for manipulating paired-genomic-loci data. Source code, an in-depth manual, and a tutorial are available publicly at www.github.com/billgreenwald/pgltools, and a python module of the operations can be installed from PyPI via the PyGLtools module. |
format | Online Article Text |
id | pubmed-5384132 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53841322017-04-12 Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data Greenwald, William W. Li, He Smith, Erin N. Benaglio, Paola Nariai, Naoki Frazer, Kelly A. BMC Bioinformatics Software BACKGROUND: Genomic interaction studies use next-generation sequencing (NGS) to examine the interactions between two loci on the genome, with subsequent bioinformatics analyses typically including annotation, intersection, and merging of data from multiple experiments. While many file types and analysis tools exist for storing and manipulating single locus NGS data, there is currently no file standard or analysis tool suite for manipulating and storing paired-genomic-loci: the data type resulting from “genomic interaction” studies. As genomic interaction sequencing data are becoming prevalent, a standard file format and tools for working with these data conveniently and efficiently are needed. RESULTS: This article details a file standard and novel software tool suite for working with paired-genomic-loci data. We present the paired-genomic-loci (PGL) file standard for genomic-interactions data, and the accompanying analysis tool suite “pgltools”: a cross platform, pypy compatible python package available both as an easy-to-use UNIX package, and as a python module, for integration into pipelines of paired-genomic-loci analyses. CONCLUSIONS: Pgltools is a freely available, open source tool suite for manipulating paired-genomic-loci data. Source code, an in-depth manual, and a tutorial are available publicly at www.github.com/billgreenwald/pgltools, and a python module of the operations can be installed from PyPI via the PyGLtools module. BioMed Central 2017-04-07 /pmc/articles/PMC5384132/ /pubmed/28388874 http://dx.doi.org/10.1186/s12859-017-1621-0 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Greenwald, William W. Li, He Smith, Erin N. Benaglio, Paola Nariai, Naoki Frazer, Kelly A. Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data |
title | Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data |
title_full | Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data |
title_fullStr | Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data |
title_full_unstemmed | Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data |
title_short | Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data |
title_sort | pgltools: a genomic arithmetic tool suite for manipulation of hi-c peak and other chromatin interaction data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5384132/ https://www.ncbi.nlm.nih.gov/pubmed/28388874 http://dx.doi.org/10.1186/s12859-017-1621-0 |
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