Gonomics: uniting high performance and readability for genomics with Go.

Gonomics: uniting high performance and readability for genomics with Go.
复制标题

Gonomics:与GO结合基因组学的高性能和可读性。

DOI:
10.1093/bioinformatics/btad516
复制
发表时间:
2023-08-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
通讯作者:
--
中科院分区:
其他
文献类型:
--
作者:

文献摘要

参考文献

相似文献

许多现有的基因组学软件库要求研究人员在相互竞争的考虑因素之间进行选择:编译语言的性能和解释语言的可访问性。Go是一种现代编译语言,它提供了解决这种冲突的机会。我们介绍Gonomics,一个开源的命令行程序和生物信息学库的集合,它在Go中实现,将可读性和性能结合起来,用于基因组分析。Gonomics包含用于读取、写入和操作各种文件格式(例如FASTA、FASTQ、BED、BEDPE、SAM、BAM和VCF)的软件包,并且可以在这些格式之间进行转换和接口。此外,我们的模块化库结构为研究人员开发自己的软件工具以解决特定问题提供了灵活的平台。这些命令可以组合并纳入复杂的管道中,以满足对高性能生物信息资源日益增长的需求。Gonomics是用Go编程语言实现的。源代码、安装说明和文档可在https://github.com/vertgenlab/gonomics上免费获得。
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. Gonomics is implemented in the Go programming language. Source code, installation instructions, and documentation are freely available at https://github.com/vertgenlab/gonomics.
DOI: 10.1093/bioinformatics/btq033
发表时间: 2010-03-15
期刊: Bioinformatics (Oxford, England)
影响因子: --
作者:
Quinlan AR;Hall IM
通讯作者: Hall IM
DOI: 10.1186/s13059-016-0974-4
发表时间: 2016-06-06
期刊: Genome biology
影响因子: 12.3
作者:
McLaren W;Gil L;Hunt SE;Riat HS;Ritchie GR;Thormann A;Flicek P;Cunningham F
通讯作者: Cunningham F
Biopython:用于计算分子生物学和生物信息学的免费 Python 工具。
DOI: 10.1093/bioinformatics/btp163
发表时间: 2009-06-01
期刊: Bioinformatics (Oxford, England)
影响因子: --
作者:
Cock PJ;Antao T;Chang JT;Chapman BA;Cox CJ;Dalke A;Friedberg I;Hamelryck T;Kauff F;Wilczynski B;de Hoon MJ
通讯作者: de Hoon MJ
DOI: 10.1177/1176934319869015
发表时间: 2019-08-15
影响因子: 2.6
作者:
Costanza, Pascal;Herzeel, Charlotte;Verachtert, Wilfried
通讯作者: Verachtert, Wilfried
DOI: 10.1038/s41586-021-03562-8
发表时间: 2021-06
期刊: Nature
影响因子: 64.8
作者:
Ren AA;Snellings DA;Su YS;Hong CC;Castro M;Tang AT;Detter MR;Hobson N;Girard R;Romanos S;Lightle R;Moore T;Shenkar R;Benavides C;Beaman MM;Müller-Fielitz H;Chen M;Mericko P;Yang J;Sung DC;Lawton MT;Ruppert JM;Schwaninger M;Körbelin J;Potente M;Awad IA;Marchuk DA;Kahn ML
通讯作者: Kahn ML