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An educational guide for nanopore sequencing in the classroom
Author(s) -
Alex Salazar,
Franklin L. Nóbrega,
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
Publication year - 2020
Publication title -
plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1007314
Subject(s) - pace , nanopore sequencing , data science , computer science , software , dna sequencing , artificial intelligence , biology , dna , geodesy , genetics , programming language , geography
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.

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