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An educational guide for nanopore sequencing in the classroom

Journal Article (2020)
Author(s)

Alex N. Salazar (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Franklin L. Nobrega (Kavli institute of nanoscience Delft, TU Delft - Applied Sciences)

Christine Anyansi (TU Delft - Electrical Engineering, Mathematics and Computer Science, Broad Institute of MIT and Harvard)

Cristian Aparicio-Maldonado (Kavli institute of nanoscience Delft, TU Delft - Applied Sciences)

Ana Rita Costa (Kavli institute of nanoscience Delft, TU Delft - Applied Sciences)

Anna C. Haagsma (TU Delft - BN/Technici en Analisten, Kavli institute of nanoscience Delft)

Anwar Hiralal (Kavli institute of nanoscience Delft, TU Delft - Applied Sciences)

Ahmed Mahfouz (Leiden University Medical Center, TU Delft - Electrical Engineering, Mathematics and Computer Science)

Rebecca E. McKenzie (Kavli institute of nanoscience Delft, TU Delft - Applied Sciences)

Teunke van Rossum (Kavli institute of nanoscience Delft, TU Delft - Applied Sciences)

Stan J.J. Brouns (TU Delft - Applied Sciences, Kavli institute of nanoscience Delft)

Thomas Abeel (Broad Institute of MIT and Harvard, TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Pattern Recognition and Bioinformatics
DOI related publication
https://doi.org/10.1371/journal.pcbi.1007314 Final published version
More Info
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Publication Year
2020
Language
English
Research Group
Pattern Recognition and Bioinformatics
Issue number
1
Volume number
16
Article number
e1007314
Pages (from-to)
e1007314
Downloads counter
428
Collections
Institutional Repository
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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.