Blog / COG Train

24 Jun 2022

Maximising access to SARS-CoV-2 bioinformatics training: What are distributed classrooms?

COG-Train’s ambition is to provide high quality, open-access training across the world, on all aspects of SARS-CoV-2 sequencing and bioinformatics. Key to this is having a model which supports a standardised approach to training that is not limited by geography.

Accordingly, we have adopted a distributed classrooms model. This allows a small training team to connect with a large audience, helping to increase the reach and impact of learning materials. It also enables training to be delivered simultaneously in multiple classrooms across the world.

How do Distributed Classrooms work?

The two core elements of our distributed classroom include:

  • Instructors (training team): who develop the core content for our COG-Train courses, assignments, and assessments.
  • Classroom Hosts: who support the learners locally, helping them to stay on track during courses and answering any general queries they might have.

Instructors upload all course materials onto a ‘Learning Management System’, through which learners are able to communicate directly with the Instructors. Instructors and learners also interact through sessions using virtual meeting software, such as Zoom.

Figure 1: Diagram explaining how Distributed Classrooms are set-up to support COG-Train courses

 

The importance of Classroom Hosts, and why we need more

Classroom Hosts help to facilitate the courses, support learners and ensure that we can maintain the capability to deliver SARS-CoV-2 genomics training globally. As we continue to expand the COG-Train courses by subject and geographies, we are always looking for more Classroom Hosts.

More details about the course programme and schedule are available via the course website.

To register your interest in becoming a COG-Train Classroom Host, please complete our form here.

The Distributed Classroom model was originally developed by H3ABioNet. Verena Ras, bioinformatics training and outreach coordinator at H3ABioNet (University of Cape Town), who has been implementing this model in Africa, noted “The H3ABioNet multiple-delivery-mode training model (as it was originally named) has helped H3ABioNet expand their training to an increasing number of institutions and countries across Africa since the model’s inception in 2016.”

The model has been used to teach several introductory and advanced training courses. In its first year of implementation, H3ABioNet focused on teaching an Introduction to Bioinformatics Training Course reaching around 360 participants across 20 classrooms in 10 African countries. The course ran for 3 months with biweekly contact sessions of 4 hours each. “This course has grown yearly, and we now reach more than 1200 participants per year across 50 classrooms” points out Verena.

“The model is highly adaptable, and we have already used it to deliver training in high-performance computing, which is still largely inaccessible to many participants based in low- and middle-income countries and regions with limited computational capacity. After our recent successes with the model, I encourage everyone based in resource-limited settings to consider taking up and pioneering the model within their region” comments Verena. The impacts of the model are threefold: access to expert scientists who develop high quality materials to train new and aspiring bioinformaticians; assist local teams in gaining the necessary experience in managing and delivering these kinds of trainings; and the formation of a community with the shared goal of advancing capacity for bioinformatics.

 

Learn more about the distributed classrooms model in the refences below:

Aron, S., Chauke, P. A., Ras, V., Panji, S., Johnston, K., & Mulder, N. (2021). The Development of a Sustainable Bioinformatics Training Environment Within the H3Africa Bioinformatics Network (H3ABioNet). In Frontiers in Education (p. 356). Frontiers. https://doi.org/10.3389/feduc.2021.725702

Gurwitz, K. T., Aron, S., Panji, S., Maslamoney, S., Fernandes, P. L., Judge, D. P., … & H3ABioNet Consortium’s Education Training and Working Group as members of the H3Africa Consortium. (2017). Designing a course model for distance-based online bioinformatics training in Africa: The H3ABioNet experience. PLoS computational biology13(10), e1005715. https://doi.org/10.1371/journal.pcbi.1005715

Ras, V., Botha, G., Aron, S., Lennard, K., Allali, I., Claassen-Weitz, S., … & Mulder, N. (2021). Using a multiple-delivery-mode training approach to develop local capacity and infrastructure for advanced bioinformatics in Africa. PLoS computational biology17(02), e1008640. https://doi.org/10.1371/journal.pcbi.1008640

 

Working together to build networks in genomics and bioinformatics:

 


COVID-19 Genomics UK (COG-UK)

The COVID-19 Genomics UK (COG-UK) consortium works in partnership to harness the power of SARS-CoV-2 genomics in the fight against COVID-19.

Led by Professor Sharon Peacock of the University of Cambridge, COG-UK is made up of an innovative collaboration of NHS organisations, the four public health agencies of the UK, the Wellcome Sanger Institute and sixteen academic partners. A full list of collaborators can be found here.

The COVID-19 pandemic, caused by SARS-CoV-2, represents a major threat to health. The COG-UK consortium was formed in March 2020 to deliver SARS-CoV-2 genome sequencing and analysis to inform public health policy and to support the establishment of a national pathogen sequencing service, with sequence data now predominantly generated by the Wellcome Sanger Institute and the Public Health Agencies.

SARS-CoV-2 genome sequencing and analysis plays a key role in the COVID-19 public health response by enabling the identification, tracking and analysis of variants of concern, and by informing the design of vaccines and therapeutics. COG-UK works collaboratively to deliver world-class research on pathogen sequencing and analysis, maximise the value of genomic data by ensuring fair access and data linkage, and provide a training programme to enable equity in global sequencing.