Software pipelines have become almost standardized tools for microbiome analysis. Currently, many pipelines are available, often sharing some of the same algorithms as stages. This is largely because each pipeline has its own source language and file formats, making it typically more economical to reinvent the wheel than to learn and interface to an existing package. With PluMA and its online plugin pool, algorithm designers can easily plug-and-play existing pipeline stages with no knowledge of their underlying implementation, allowing them to efficiently test a new algorithm alongside these stages or combine them in a new and creative way. The current project demonstrated the usefulness of PluMA through an example pipeline (P-M16S) that expands an obesity study involving gut microbiome samples from the mouse by integrating multiple plugins, using a variety of source languages and file formats, producing new results. Links to github repositories for the PluMA source code and P-M16S, in addition to the plugin pool are available from the Bioinformatics Research Group (BioRG) at: http://biorg.cis.fiu.edu/pluma. (publisher abstract modified)
Constructing Lightweight and Flexible Pipelines Using Plugin-Based Microbiome Analysis (PluMA)
NCJ Number
253163
Journal
Bioinformatics Volume: 34 Issue: 17 Dated: 2018 Pages: 2881-2888
Date Published
2018
Length
8 pages
Annotation
This article presents Plugin-Based Microbiome Analysis (PluMA), which provides a lightweight back end that can be infinitely extended using dynamically loaded plugin extensions that can be written in one of many compiled or scripting languages.
Abstract
Date Published: January 1, 2018