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Gonomics: uniting high performance and readability for genomics with Go

SUMMARY: Many existing software libraries for genomics require researchers to pick between competing considerations: the performance of compiled languages and the accessibility of interpreted languages. Go, a modern compiled language, provides an opportunity to address this conflict. We introduce Go...

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Autores principales: Au, Eric H, Fauci, Christiana, Luo, Yanting, Mangan, Riley J, Snellings, Daniel A, Shoben, Chelsea R, Weaver, Seth, Simpson, Shae K, Lowe, Craig B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10466080/
https://www.ncbi.nlm.nih.gov/pubmed/37624924
http://dx.doi.org/10.1093/bioinformatics/btad516
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author Au, Eric H
Fauci, Christiana
Luo, Yanting
Mangan, Riley J
Snellings, Daniel A
Shoben, Chelsea R
Weaver, Seth
Simpson, Shae K
Lowe, Craig B
author_facet Au, Eric H
Fauci, Christiana
Luo, Yanting
Mangan, Riley J
Snellings, Daniel A
Shoben, Chelsea R
Weaver, Seth
Simpson, Shae K
Lowe, Craig B
author_sort Au, Eric H
collection PubMed
description SUMMARY: Many existing software libraries for genomics require researchers to pick between competing considerations: the performance of compiled languages and the accessibility of interpreted languages. Go, a modern compiled language, provides an opportunity to address this conflict. We introduce Gonomics, an open-source collection of command line programs and bioinformatic libraries implemented in Go that unites readability and performance for genomic analyses. Gonomics contains packages to read, write, and manipulate a wide array of file formats (e.g. FASTA, FASTQ, BED, BEDPE, SAM, BAM, and VCF), and can convert and interface between these formats. Furthermore, our modular library structure provides a flexible platform for researchers developing their own software tools to address specific questions. These commands can be combined and incorporated into complex pipelines to meet the growing need for high-performance bioinformatic resources. AVAILABILITY AND IMPLEMENTATION: Gonomics is implemented in the Go programming language. Source code, installation instructions, and documentation are freely available at https://github.com/vertgenlab/gonomics.
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spelling pubmed-104660802023-08-31 Gonomics: uniting high performance and readability for genomics with Go Au, Eric H Fauci, Christiana Luo, Yanting Mangan, Riley J Snellings, Daniel A Shoben, Chelsea R Weaver, Seth Simpson, Shae K Lowe, Craig B Bioinformatics Applications Note SUMMARY: Many existing software libraries for genomics require researchers to pick between competing considerations: the performance of compiled languages and the accessibility of interpreted languages. Go, a modern compiled language, provides an opportunity to address this conflict. We introduce Gonomics, an open-source collection of command line programs and bioinformatic libraries implemented in Go that unites readability and performance for genomic analyses. Gonomics contains packages to read, write, and manipulate a wide array of file formats (e.g. FASTA, FASTQ, BED, BEDPE, SAM, BAM, and VCF), and can convert and interface between these formats. Furthermore, our modular library structure provides a flexible platform for researchers developing their own software tools to address specific questions. These commands can be combined and incorporated into complex pipelines to meet the growing need for high-performance bioinformatic resources. AVAILABILITY AND IMPLEMENTATION: Gonomics is implemented in the Go programming language. Source code, installation instructions, and documentation are freely available at https://github.com/vertgenlab/gonomics. Oxford University Press 2023-08-25 /pmc/articles/PMC10466080/ /pubmed/37624924 http://dx.doi.org/10.1093/bioinformatics/btad516 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://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 Note
Au, Eric H
Fauci, Christiana
Luo, Yanting
Mangan, Riley J
Snellings, Daniel A
Shoben, Chelsea R
Weaver, Seth
Simpson, Shae K
Lowe, Craig B
Gonomics: uniting high performance and readability for genomics with Go
title Gonomics: uniting high performance and readability for genomics with Go
title_full Gonomics: uniting high performance and readability for genomics with Go
title_fullStr Gonomics: uniting high performance and readability for genomics with Go
title_full_unstemmed Gonomics: uniting high performance and readability for genomics with Go
title_short Gonomics: uniting high performance and readability for genomics with Go
title_sort gonomics: uniting high performance and readability for genomics with go
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10466080/
https://www.ncbi.nlm.nih.gov/pubmed/37624924
http://dx.doi.org/10.1093/bioinformatics/btad516
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