{"title":"stana:一个基于临床数据的元基因型分析和交互式应用程序的R包。","authors":"Noriaki Sato, Kotoe Katayama, Daichi Miyaoka, Miho Uematsu, Ayumu Saito, Kosuke Fujimoto, Satoshi Uematsu, Seiya Imoto","doi":"10.1093/nargab/lqae191","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":33994,"journal":{"name":"NAR Genomics and Bioinformatics","volume":"7 1","pages":"lqae191"},"PeriodicalIF":4.0000,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11707543/pdf/","citationCount":"0","resultStr":"{\"title\":\"stana: an R package for metagenotyping analysis and interactive application based on clinical data.\",\"authors\":\"Noriaki Sato, Kotoe Katayama, Daichi Miyaoka, Miho Uematsu, Ayumu Saito, Kosuke Fujimoto, Satoshi Uematsu, Seiya Imoto\",\"doi\":\"10.1093/nargab/lqae191\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":33994,\"journal\":{\"name\":\"NAR Genomics and Bioinformatics\",\"volume\":\"7 1\",\"pages\":\"lqae191\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2025-01-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11707543/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NAR Genomics and Bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/nargab/lqae191\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/3/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NAR Genomics and Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/nargab/lqae191","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
stana: an R package for metagenotyping analysis and interactive application based on clinical data.
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.