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样本中微生物分类的组成分析。来自大型人类微生物组研究的越来越多的证据表明,肠道微生物组变化的功能后果可能为研究它们对炎症和免疫反应的影响提供更多的权力。虽然16S rRNA分析是描述微生物成分的最流行和最经济的方法之一,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。已开发了用于从16S rRNA基因数据中预测微生物组功能的生物信息学工具。其中,PICRUSt2已成为最受欢迎的功能配置文件预测工具之一,可生成社区范围的通路丰度。然而,在比较组之间测试通路丰度差异的情况下,没有最先进的推断工具。我们开发了ggpicrust2,一个R软件包,进行广泛的差异丰度(DA)分析并提供可发布的可视化方法来突出显示信号。