An educational guide for nanopore sequencing in the classroom

Alex N. Salazar, Franklin L. Nobrega, Christine Anyansi, Cristian Aparicio-Maldonado, Ana Rita Costa, Anna C. Haagsma, Anwar Hiralal, Ahmed Mahfouz, Rebecca E. McKenzie, Teunke van Rossum, Stan J.J. Brouns, Thomas Abeel

Research output: Contribution to journalArticleScientificpeer-review

13 Citations (Scopus)
163 Downloads (Pure)

Abstract

The last decade has witnessed a remarkable increase in our ability to measure genetic information. Advancements of sequencing technologies are challenging the existing methods of data storage and analysis. While methods to cope with the data deluge are progressing, many biologists have lagged behind due to the fast pace of computational advancements and tools available to address their scientific questions. Future generations of biologists must be more computationally aware and capable. This means they should be trained to give them the computational skills to keep pace with technological developments. Here, we propose a model that bridges experimental and bioinformatics concepts using the Oxford Nanopore Technologies (ONT) sequencing platform. We provide both a guide to begin to empower the new generation of educators, scientists, and students in performing long-read assembly of bacterial and bacteriophage genomes and a standalone virtual machine containing all the required software and learning materials for the course.

Original languageEnglish
Article numbere1007314
Pages (from-to)e1007314
Number of pages7
JournalPLoS Computational Biology
Volume16
Issue number1
DOIs
Publication statusPublished - 2020

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