{"title":"在线和面对面本科科学课程中使用免费网络工具分析微生物组","authors":"A. Zelaya, N. Gerardo, L. Blumer, C. Beck","doi":"10.24918/cs.2022.35","DOIUrl":null,"url":null,"abstract":"Our understanding of microbiomes, or the collection of microorganisms and their genes in a given environment, has been revolutionized by technological and computational advances. However, many undergraduate students do not get hands-on experiences with processing, analyzing, or interpreting these types of datasets. Recent global events have increased the need for effective educational activities that can be performed virtually and remotely. Here, we present a module that introduces STEM undergraduates to the bioinformatic and statistical analyses of bacterial communities using a combination of free, web-based data processing software. These lessons allow students to engage with the studies of microbiomes; gain valuable experiences processing large, high-throughput datasets; and practice their science communication skills. The lessons presented here walk students through two web-based platforms. The first ( DNA Subway ) is an easy-to-use wrapper of the popular QIIME (pronounced “chime”) pipeline, which performs quality control analysis of the raw sequence data and outputs a community matrix file with assigned bacterial taxonomies. The second, ranacapa , is an R Shiny App that allows students to compare microbial communities, perform statistical analyses and visualize community data. Students may communicate their findings with a written final report or oral presentation. While the lessons presented here use a sample dataset based on the gut-microbiome of the bean beetle ( Callosobruchus maculatus ), the materials are easily modified to use original next- generation amplicon sequence data from any host or environment. Additionally, options for alternative datasets are also provided facilitating flexibility within the curriculum.","PeriodicalId":72713,"journal":{"name":"CourseSource","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of Microbiomes Using Free Web-Based Tools in Online and In-Person Undergraduate Science Courses\",\"authors\":\"A. Zelaya, N. Gerardo, L. Blumer, C. Beck\",\"doi\":\"10.24918/cs.2022.35\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Our understanding of microbiomes, or the collection of microorganisms and their genes in a given environment, has been revolutionized by technological and computational advances. However, many undergraduate students do not get hands-on experiences with processing, analyzing, or interpreting these types of datasets. Recent global events have increased the need for effective educational activities that can be performed virtually and remotely. Here, we present a module that introduces STEM undergraduates to the bioinformatic and statistical analyses of bacterial communities using a combination of free, web-based data processing software. These lessons allow students to engage with the studies of microbiomes; gain valuable experiences processing large, high-throughput datasets; and practice their science communication skills. The lessons presented here walk students through two web-based platforms. The first ( DNA Subway ) is an easy-to-use wrapper of the popular QIIME (pronounced “chime”) pipeline, which performs quality control analysis of the raw sequence data and outputs a community matrix file with assigned bacterial taxonomies. The second, ranacapa , is an R Shiny App that allows students to compare microbial communities, perform statistical analyses and visualize community data. Students may communicate their findings with a written final report or oral presentation. While the lessons presented here use a sample dataset based on the gut-microbiome of the bean beetle ( Callosobruchus maculatus ), the materials are easily modified to use original next- generation amplicon sequence data from any host or environment. Additionally, options for alternative datasets are also provided facilitating flexibility within the curriculum.\",\"PeriodicalId\":72713,\"journal\":{\"name\":\"CourseSource\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CourseSource\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24918/cs.2022.35\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CourseSource","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24918/cs.2022.35","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of Microbiomes Using Free Web-Based Tools in Online and In-Person Undergraduate Science Courses
Our understanding of microbiomes, or the collection of microorganisms and their genes in a given environment, has been revolutionized by technological and computational advances. However, many undergraduate students do not get hands-on experiences with processing, analyzing, or interpreting these types of datasets. Recent global events have increased the need for effective educational activities that can be performed virtually and remotely. Here, we present a module that introduces STEM undergraduates to the bioinformatic and statistical analyses of bacterial communities using a combination of free, web-based data processing software. These lessons allow students to engage with the studies of microbiomes; gain valuable experiences processing large, high-throughput datasets; and practice their science communication skills. The lessons presented here walk students through two web-based platforms. The first ( DNA Subway ) is an easy-to-use wrapper of the popular QIIME (pronounced “chime”) pipeline, which performs quality control analysis of the raw sequence data and outputs a community matrix file with assigned bacterial taxonomies. The second, ranacapa , is an R Shiny App that allows students to compare microbial communities, perform statistical analyses and visualize community data. Students may communicate their findings with a written final report or oral presentation. While the lessons presented here use a sample dataset based on the gut-microbiome of the bean beetle ( Callosobruchus maculatus ), the materials are easily modified to use original next- generation amplicon sequence data from any host or environment. Additionally, options for alternative datasets are also provided facilitating flexibility within the curriculum.