Teaching Genomics to Life Science Undergraduates Using Cloud Computing Platforms with Open Datasets

Autor/inn/en	Poolman, Toryn M.; Townsend-Nicholson, Andrea; Cain, Amanda
Titel	Teaching Genomics to Life Science Undergraduates Using Cloud Computing Platforms with Open Datasets
Quelle	In: Biochemistry and Molecular Biology Education, 50 (2022) 5, S.446-449 (4 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Poolman, Toryn M.) ORCID (Townsend-Nicholson, Andrea)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1470-8175
DOI	10.1002/bmb.21646
Schlagwörter	Genetics; Undergraduate Students; Biological Sciences; Internet; Computer Software; Educational Technology; Science Activities; Data Analysis + Suchen Sie Ihr Suchwort? Humangenetik; Abwasserbiologie; Unterrichtsmedien; Auswertung
Abstract	The final year of a biochemistry degree is usually a time to experience research. However, laboratory-based research projects were not possible during COVID-19. Instead, we used open datasets to provide computational research projects in metagenomics to biochemistry undergraduates (80 students with limited computing experience). We aimed to give the students a chance to explore any dataset, rather than use a small number of artificial datasets ([approximately]60 published datasets were used). To achieve this, we utilized Google Colaboratory (Colab), a virtual computing environment. Colab was used as a framework to retrieve raw sequencing data (analyzed with QIIME2) and generate visualizations. Setting up the environment requires no prior experience; all students have the same drive structure and notebooks can be shared (for synchronous sessions). We also used the platform to combine multiple datasets, perform a meta-analysis, and allowed the students to analyze large datasets with 1000s of subjects and factors. Projects that required increased computational resources were integrated with Google Cloud Compute. In future, all research projects can include some aspects of reanalyzing public data, providing students with data science experience. Colab is also an excellent environment in which to develop data skills in multiple languages (e.g., Perl, Python, Julia). (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01