Gonomics: uniting high performance and readability for genomics with Go

Abstract 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 intr...

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Bibliographic Details
Published in:	Bioinformatics (Oxford, England) Vol. 39; no. 8
Main Authors:	Au, Eric H, Fauci, Christiana, Luo, Yanting, Mangan, Riley J, Snellings, Daniel A, Shoben, Chelsea R, Weaver, Seth, Simpson, Shae K, Lowe, Craig B
Format:	Journal Article
Language:	English
Published:	England Oxford University Press 01-08-2023
Subjects:	Applications Note Comprehension Computational Biology Documentation Genomics Programming Languages
Online Access:	Get full text
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Summary:	Abstract 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. Graphical abstract
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 These authors represent the lead development team and are listed alphabetically. Present address for Eric H Au: Mammoth Biosciences, Inc., Brisbane, CA 94005, USA Present address for Daniel A Snellings: Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
ISSN:	1367-4811 1367-4803 1367-4811
DOI:	10.1093/bioinformatics/btad516