TaxSEA: rapid interpretation of microbiome alterations using taxon set enrichment analysis and public databases.

IF 6.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Cong M Pham, Timothy J Rankin, Timothy P Stinear, Calum J Walsh, Feargal J Ryan
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引用次数: 0

Abstract

Microbial communities are essential regulators of ecosystem function, with their composition commonly assessed through DNA sequencing. Most current tools focus on detecting changes among individual taxa (e.g. species or genera), however in other omics fields, such as transcriptomics, enrichment analyses like gene set enrichment analysis are commonly used to uncover patterns not seen with individual features. Here, we introduce TaxSEA, a taxon set enrichment analysis tool available as an R package, a web portal (https://shiny.taxsea.app), and a Python package. TaxSEA integrates taxon sets from five public microbiota databases (BugSigDB, MiMeDB, GutMGene, mBodyMap, and GMRepoV2) while also allowing users to incorporate custom sets such as taxonomic groupings. In silico assessments show TaxSEA is accurate across a range of set sizes. When applied to differential abundance analysis output from inflammatory bowel disease and type 2 diabetes metagenomic data, TaxSEA can rapidly identify changes in functional groups corresponding to known associations. We also show that TaxSEA is robust to the choice of differential abundance analysis package. In summary, TaxSEA enables researchers to efficiently contextualize their findings within the broader microbiome literature, facilitating rapid interpretation, and advancing understanding of microbiome-host and environmental interactions.

TaxSEA:利用分类单元集富集分析和公共数据库快速解释微生物组变化。
微生物群落是生态系统功能的重要调节者,其组成通常通过DNA测序来评估。目前大多数工具集中于检测单个分类群(如种或属)之间的变化,然而在其他组学领域,如转录组学,富集分析(如基因集富集分析)通常用于揭示个体特征中未见的模式。在这里,我们介绍TaxSEA,这是一个分类单元集丰富分析工具,可以作为R包、web门户(https://shiny.taxsea.app)和Python包获得。TaxSEA集成了来自五个公共微生物数据库(BugSigDB, MiMeDB, GutMGene, mBodyMap和GMRepoV2)的分类群集,同时还允许用户合并自定义集,如分类分组。计算机评估表明TaxSEA在一系列集合大小上是准确的。当应用于炎性肠病和2型糖尿病宏基因组数据的差异丰度分析输出时,TaxSEA可以快速识别与已知关联相对应的功能群的变化。我们还表明TaxSEA对差异丰度分析软件包的选择具有鲁棒性。总之,TaxSEA使研究人员能够有效地将他们的发现置于更广泛的微生物组文献中,促进快速解释,并推进对微生物组-宿主和环境相互作用的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Briefings in bioinformatics
Briefings in bioinformatics 生物-生化研究方法
CiteScore
13.20
自引率
13.70%
发文量
549
审稿时长
6 months
期刊介绍: Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data. The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.
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