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一种采用课程生物信息学方法教授本科生使用R语言分析宏基因组数据集的方式。

A Curricular Bioinformatics Approach to Teaching Undergraduates to Analyze Metagenomic Datasets Using R.

作者信息

Kruchten Anne E

机构信息

Department of Biology, The College of St. Scholastica, Duluth, MN, United States.

出版信息

Front Microbiol. 2020 Sep 10;11:578600. doi: 10.3389/fmicb.2020.578600. eCollection 2020.

Abstract

Biologists with bioinformatic skills will be better prepared for the job market, but relatively few biology programs require bioinformatics courses. Inclusion in the curriculum may be hindered by several barriers, including lack of faculty expertise, student resistance to computational work, and few examples in the pedagogical literature. An 8-week wet-lab and research experience for undergraduates was implemented. Students performed DNA purification and metagenomics analysis to compare the diversity and abundance of microbes in two samples. Students sampled snow from sites in northern Minnesota and purified genomic DNA from the microbes, followed by metagenomic analysis. Students used an existing metagenomic dataset to practice analysis skills, including comparing the use of Excel versus R for analysis and visualization of a large dataset. Upon receipt of the snow data, students applied their recently acquired skills to their new dataset and reported their results via a poster. Several outcomes were achieved as a result of this module. First, YouTube videos demonstrating hands-on metagenomics and R techniques were used as professional development for faculty, leading to broadened research capabilities and comfort with bioinformatics. Second, students were introduced to computational skills in a manner that was intentional, with time for both introduction reinforcement of skills. Finally, the module was effectively included in a biology curriculum because it could function as either a stand-alone course or a module within another course such as microbiology. This module, developed with Course-based Undergraduate Research Experience guidelines in mind, introduces students and faculty to bioinformatics in biology research.

摘要

具备生物信息学技能的生物学家在就业市场上会更具优势,但相对较少的生物学专业课程要求开设生物信息学课程。课程纳入可能受到几个障碍的阻碍,包括教师专业知识的缺乏、学生对计算工作的抵触以及教学文献中的实例较少。开展了一个为期8周的本科生湿实验室和研究体验项目。学生们进行了DNA纯化和宏基因组分析,以比较两个样本中微生物的多样性和丰度。学生们从明尼苏达州北部的地点采集雪样,从微生物中纯化基因组DNA,然后进行宏基因组分析。学生们使用现有的宏基因组数据集来练习分析技能,包括比较使用Excel和R对大型数据集进行分析和可视化。收到雪样数据后,学生们将新学到的技能应用到新的数据集中,并通过海报展示了他们的结果。由于这个模块,取得了几个成果。首先,展示宏基因组学和R技术实际操作的YouTube视频被用作教师的专业发展资源,拓宽了他们的研究能力并增强了他们对生物信息学的熟悉程度。其次,以一种有针对性的方式向学生介绍了计算技能,并有时间进行技能的介绍和强化。最后,该模块有效地纳入了生物学课程,因为它既可以作为一门独立课程,也可以作为微生物学等另一门课程中的一个模块。这个模块是按照基于课程的本科研究体验指导方针开发的,将学生和教师引入生物学研究中的生物信息学领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b78/7511545/f10312d44246/fmicb-11-578600-g001.jpg

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