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ggpicrust2:一个用于 PICRUSt2 预测功能谱分析和可视化的 R 包。

ggpicrust2: an R package for PICRUSt2 predicted functional profile analysis and visualization.

机构信息

Department of Biostatistics, Southern Medical University, Guangzhou 510515, China.

Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH 45221, United States.

出版信息

Bioinformatics. 2023 Aug 1;39(8). doi: 10.1093/bioinformatics/btad470.

Abstract

SUMMARY

Microbiome research is now moving beyond the compositional analysis of microbial taxa in a sample. Increasing evidence from large human microbiome studies suggests that functional consequences of changes in the intestinal microbiome may provide more power for studying their impact on inflammation and immune responses. Although 16S rRNA analysis is one of the most popular and a cost-effective method to profile the microbial compositions, marker-gene sequencing cannot provide direct information about the functional genes that are present in the genomes of community members. Bioinformatic tools have been developed to predict microbiome function with 16S rRNA gene data. Among them, PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) has become one of the most popular functional profile prediction tools, which generates community-wide pathway abundances. However, no state-of-art inference tools are available to test the differences in pathway abundances between comparison groups. We have developed ggpicrust2, an R package, for analyzing functional profiles derived from 16S rRNA sequencing. This powerful tool enables researchers to conduct extensive differential abundance analyses and generate visually appealing visualizations that effectively highlight functional signals. With ggpicrust2, users can obtain publishable results and gain deeper insights into the functional composition of their microbial communities.

AVAILABILITY AND IMPLEMENTATION

The package is open-source under the MIT and file license and is available at CRAN and https://github.com/cafferychen777/ggpicrust2. Its shiny web is available at https://a95dps-caffery-chen.shinyapps.io/ggpicrust2_shiny/.

摘要

摘要

微生物组研究现在已经超越了对样本中微生物分类群组成的分析。越来越多的大型人类微生物组研究证据表明,肠道微生物组的功能变化可能为研究其对炎症和免疫反应的影响提供更大的动力。虽然 16S rRNA 分析是最受欢迎和具有成本效益的方法之一,可以分析微生物组成,但标记基因测序不能提供存在于群落成员基因组中的功能基因的直接信息。已经开发了生物信息学工具来预测 16S rRNA 基因数据的微生物组功能。其中,PICRUSt2(通过未观察状态的重建来研究群落的系统发育)已成为最受欢迎的功能谱预测工具之一,它生成了全社区途径丰度。然而,目前还没有先进的推断工具可用于测试比较组之间途径丰度的差异。我们开发了 ggpicrust2,这是一个用于分析 16S rRNA 测序得出的功能谱的 R 包。这个强大的工具使研究人员能够进行广泛的差异丰度分析,并生成视觉上吸引人的可视化效果,有效地突出功能信号。使用 ggpicrust2,用户可以获得可发表的结果,并深入了解其微生物群落的功能组成。

可用性和实现

该软件包以 MIT 和文件许可证开源,可在 CRAN 和 https://github.com/cafferychen777/ggpicrust2 上获得。其闪亮的网络可在 https://a95dps-caffery-chen.shinyapps.io/ggpicrust2_shiny/ 上获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3be5/10425198/034b76d3fee2/btad470f1.jpg

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