MetaLAFFA: a flexible, end-to-end, distributed computing-compatible metagenomic functional annotation pipeline.
MetaLAFFA: a flexible, end-to-end, distributed computing-compatible metagenomic functional annotation pipeline.
复制标题
DOI：
10.1186/s12859-020-03815-9
复制
发表时间：
2020-10-21
影响因子：
3
通讯作者：
Borenstein E
中科院分区：
文献类型：
--
作者：
Eng A;Verster AJ;Borenstein E
近年来，微生物群落已成为跨多个学科的重要研究课题。这些群落通常通过鸟枪法宏基因组测序进行检查，这种技术可以提供对微生物群落基因组内容的独特见解。鸟枪法宏基因组数据的功能注释已成为一种越来越流行的方法，用于识别由群落组成微生物编码的聚合功能能力。然而，目前可用的宏基因组功能注释管道存在一些缺点，包括有限的管道定制选项、缺乏标准的原始序列数据预处理以及与分布式计算系统集成的能力不足。在这里，我们介绍 MetaLAFFA，一个功能注释管道，旨在以未经过滤的鸟枪法宏基因组数据作为输入并生成功能配置文件。 MetaLAFFA被实现为Snakemake管道，可以方便地与分布式计算集群集成，使用户能够充分利用可用的计算资源。默认的管道设置允许新用户按照常见做法运行MetaLAFFA，而基于Python模块的配置系统为高级用户提供灵活的管道定制界面。 MetaLAFFA 还为管道中的每个步骤生成汇总统计数据，以便用户可以更好地了解预处理和注释质量。 MetaLAFFA 是一种新的端到端宏基因组功能注释管道，具有分布式计算兼容性和灵活的定制选项。 MetaLAFFA 源代码可从 https://github.com/borenstein-lab/MetaLAFFA 获取，并且可以通过 Conda 安装，如随附文档中所述。
Microbial communities have become an important subject of research across multiple disciplines in recent years. These communities are often examined via shotgun metagenomic sequencing, a technology which can offer unique insights into the genomic content of a microbial community. Functional annotation of shotgun metagenomic data has become an increasingly popular method for identifying the aggregate functional capacities encoded by the community’s constituent microbes. Currently available metagenomic functional annotation pipelines, however, suffer from several shortcomings, including limited pipeline customization options, lack of standard raw sequence data pre-processing, and insufficient capabilities for integration with distributed computing systems. Here we introduce MetaLAFFA, a functional annotation pipeline designed to take unfiltered shotgun metagenomic data as input and generate functional profiles. MetaLAFFA is implemented as a Snakemake pipeline, which enables convenient integration with distributed computing clusters, allowing users to take full advantage of available computing resources. Default pipeline settings allow new users to run MetaLAFFA according to common practices while a Python module-based configuration system provides advanced users with a flexible interface for pipeline customization. MetaLAFFA also generates summary statistics for each step in the pipeline so that users can better understand pre-processing and annotation quality. MetaLAFFA is a new end-to-end metagenomic functional annotation pipeline with distributed computing compatibility and flexible customization options. MetaLAFFA source code is available at https://github.com/borenstein-lab/MetaLAFFA and can be installed via Conda as described in the accompanying documentation.
登录
查看更多内容
影响因子：
48
作者：
Langmead, Ben;Salzberg, Steven L.
通讯作者：
Salzberg, Steven L.
影响因子：
15.5
作者：
Manor O;Borenstein E
通讯作者：
Borenstein E
影响因子：
10.7
作者：
Huerta-Cepas J;Forslund K;Coelho LP;Szklarczyk D;Jensen LJ;von Mering C;Bork P
通讯作者：
Bork P
影响因子：
12.3
作者：
Manor O;Borenstein E
通讯作者：
Borenstein E
影响因子：
64.5
作者：
Sharon, Gil;Cruz, Nikki Jamie;Mazmanian, Sarkis K.
通讯作者：
Mazmanian, Sarkis K.