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 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, to do extensive differential abundance(DA) analyses and provide publishable visualization to highlight the signals.
翻译:微生物组研究现在已经超越了对样品中微生物分类群的成分分析。来自大规模人类肠道菌群研究的越来越多证据表明,肠道菌群变化的功能后果可能提供更强的能力,以便研究其对炎症和免疫反应的影响。虽然16S rRNA分析是最受欢迎和成本效益最高的方法之一,以获得微生物组成成分剖面,但标记基因测序不能提供有关社区成员基因组中存在的功能基因的直接信息。已经开发出生物信息学工具,使用16S rRNA基因数据预测微生物组功能。其中,PICRUSt2已成为最受欢迎的功能剖面预测工具之一,可以生成社区范围的通路丰度。然而,没有最先进的推断工具可用于测试比较组之间的通路丰度差异。我们开发了ggpicrust2,一个 R 包,进行了广泛的差异丰度(DA)分析,并提供可发布的可视化以突出信号。