Sato Noriaki, Katayama Kotoe, Miyaoka Daichi, Uematsu Miho, Saito Ayumu, Fujimoto Kosuke, Uematsu Satoshi, Imoto Seiya
Division of Health Medical Intelligence, Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan.
Laboratory of Sequence Analysis, Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan.
NAR Genom Bioinform. 2025 Jan 8;7(1):lqae191. doi: 10.1093/nargab/lqae191. eCollection 2025 Mar.
Metagenotyping of metagenomic data has recently attracted increasing attention as it resolves intraspecies diversity by identifying single nucleotide variants. Furthermore, gene copy number analysis within species provides a deeper understanding of metabolic functions in microbial communities. However, a platform for examining metagenotyping results based on relevant grouping data is lacking. Here, we have developed the R package, stana, for the processing and analysis of metagenotyping results. The package consists of modules for preprocessing, statistical analysis, functional analysis and visualization. An interactive analysis environment for exploring the metagenotyping results was also developed and publicly released with over 1000 publicly available metagenome samples related to human diseases. Three examples exploring the relationship between the metagenotypes of the gut microbiome and human diseases are presented-end-stage renal disease, Crohn's disease and Parkinson's disease. The results suggest that stana facilitated the confirmation of the original study's findings and the generation of a new hypothesis. The GitHub repository for the package is available at https://github.com/noriakis/stana.
宏基因组数据的宏基因分型最近受到越来越多的关注，因为它通过识别单核苷酸变异来解析种内多样性。此外，物种内的基因拷贝数分析有助于更深入地了解微生物群落中的代谢功能。然而，目前缺乏一个基于相关分组数据来检验宏基因分型结果的平台。在此，我们开发了R包stana，用于处理和分析宏基因分型结果。该包由预处理、统计分析、功能分析和可视化模块组成。我们还开发了一个用于探索宏基因分型结果的交互式分析环境，并与1000多个与人类疾病相关的公开可用宏基因组样本一起公开发布。本文给出了三个探索肠道微生物群宏基因分型与人类疾病之间关系的例子——终末期肾病、克罗恩病和帕金森病。结果表明，stana有助于证实原研究的发现并产生新的假设。该包的GitHub存储库可在https://github.com/noriakis/stana获取。
