Gonomics: Uniting High Performance and Readability for Genomics with Go

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2023 Aug 25

PMID 37624924

Authors

Eric H Au

Christiana Fauci

Yanting Luo

Riley J Mangan

Daniel A Snellings

Chelsea R Shoben

Seth Weaver

Shae K Simpson

Craig B Lowe

Affiliations

Soon will be listed here.

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.

Citing Articles

Genome Sequence of a Marine Threespine Stickleback () from Rabbit Slough in the Cook Inlet.

Au E, Weaver S, Katikaneni A, Wucherpfennig J, Luo Y, Mangan R bioRxiv. 2025; .

PMID: 39975098 PMC: 11839064. DOI: 10.1101/2025.02.06.636934.

Epigenetic control of metabolic identity across cell types.

Pacheco M, Gerard D, Mangan R, Chapman A, Hecker D, Kellis M bioRxiv. 2024; .

PMID: 39091778 PMC: 11291179. DOI: 10.1101/2024.07.24.604914.

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