Course Overview: The Research Data Management (RDM) short course introduces the principles and practices of RDM and practical advice for implementing these practices in African research context. Topics covered include data discovery and re-use, data documentation and organization, data standards and Ontology, data storage and security, repositories and policies, FAIR & reproducibility and best practices in developing an effective DMP.

Intended Audience: The course is aimed at the graduate students and biomedical scientists who are currently working on clinical, genomics and bioinformatics projects in Africa.

Skill level of training: Beginner

Language: The course and materials are offered in English

Prerequisites: A basic background/understanding of biochemistry, molecular biology and/or genetics. Those with a computer science background with experience in bioinformatics are welcome to apply.

Type of training: Online

Venue of course: Zoom.

Dates for the course: 27-30 June 2022; from 10:00 CAT to 14:00 CAT.

Course organizers: Faisal Fadlelmola, Katherine Johnston, Verena Ras, Melek Chaouch, Lyndon Zass, Ziyaad Parker, Ayton Meintjes, Sumir Panji and Nicola Mulder

Participation: The course is available to any participant who is able to attend the Zoom sessions and the interactive hours with the course instructors for the days of the course.

Course Sponsors: H3ABioNet

Objectives: After this RDM short course participants should be able to:

1. Understand what research data management is;
2. Recognize why research data management is necessary;
3. Understand best practices and aspects for research data management; and
4. Have knowledge of the RDM tools available at your institution and online.

Course limitations: This course will only provide a foundation for continued learning in research data management and will not teach any advanced RDM aspects.

Applications are now closed

Training materials availability: Training materials for this course are not currently available.

Course Curriculum:

Module 1: Data & research life cycle

Module 2: Curation, data types and privacy issues

Module 3: Standards, taxonomy & Ontology

Module 4: Preservation, repositories, security and policies

Module 5: FAIR & Reproducibility

Module 6: Data Management Plan (DMP)

Course Schedule:

Course Overview:

Course Overview:

Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover an introduction to The Shell, Python and R. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

Keywords: Carpentries, programming, coding, novice, R, Python, linux 

Skill level of training: Beginner  

Language: English

Venue of workshop: Online via Zoom; link will be communicated to those who are accepted.

Dates for the workshop: 14 - 18 March 2022 from ~10 am – 2:30 pm all days

Registration opens:  02 March 2022 | Registration closes: 09 March 2022 | Notification date: 10 March 2022

Link to application form: This is a closed workshop aimed at students and staff at the Faculty of Health Sciences at the University of Cape Town.

Workshop trainers: Lyndon Zass, Ruth Nanjala, Verena Ras, Ichrak Benamri, Nihad Alsayed, Melek Chaouch, Ziyaad Parker, Mamana Mbiyavanga 

Workshop organisers: H3ABioNet, Verena Ras, Lyndon Zass, Nicola Martin, Darren Martin

Workshop Sponsors: H3ABioNet

Intended Audience: UCT Computational Biology Honour’s cohort + anyone else from within UCT Health Sciences who may be interested

Syllabus and Tools: please see workshop website: https://verena90.github.io/2022-03-14-online-UCT_Med/

Prerequisites: As this is presented at a novice level, no prerequisites are required but you will need to have access to a laptop where you are able to install the required software (R, Python, shell terminal). You will also need good internet access to ensure you are able to be online for the full course.

Workshop limitations: This workshop will only provide a foundation in Linux, R and Python but will not teach any advanced coding or programming. Should this be what you require, this may not be the appropriate course for you.

Training Materials Availability:

Training materials used for this course were not directly produced by H3ABioNet but may be accessed here: https://verena90.github.io/2022-03-14-online-UCT_Med/. Please note, these materials may be governed by different sharing/re-use policies, and you are encouraged to follow the policies of the external providers regarding material re-use and/or sharing.

Course Overview:

The introduction to hands-on Bioconductor workshop is a virtual two-half-day training to provide an overview of leveraging open-source Bioconductor resources for research studies.

There will be two courses offered by the BioConductor community:

• Introduction to Bioconductor Annotation Resources
  • (Thursday, 29th April)  
• Epidemiology for Bioinformaticians
  • (Friday, 30th April 2021)

Keywords: Bioinformatics, Epidemiology, study design, causal inference, BioConductor packages 

Intended Audience:

The course is designed for biomedical research graduate students (master, PhD), early-stage researchers, and bioinformaticians who would like to build their capacity in data analysis using Bioconductor resources and are familiar with R syntax and using RStudio.

Skill level of training: Intermediate

Language: The course and materials are offered in English 

Type of training:  Online

Credential awarded: Meeting participant will receive a workshop certificate.

Workshop organisers: H3Africa, H3ABioNet, and the Bioconductor Community

Proposed workshop outcomes: The proposed courses will lay a foundation on how to efficiently use open-source Bioconductor resources for bioinformatics analysis.

The course tools and packages relevant for this course will be hosted on Orchestra, an online platform for teaching and learning hands-on computational skills in self-contained and launchable workshop environments.

The course will be in two main forms which include;

• lectures to introduce basic concepts.
• demonstrations and hands-on computer practicals on analysis pipeline/workflows for mapping identifiers, querying multiple data sources, performing epidemiological causal inference, and visualizing results in high-resolution publication format.

The hands-on sessions may provide an opportunity for participants to work with their data. Instructors for the course have experience in developing and applying methods for research analysis and also involved in developing statistical methods/algorithms and Bioconductor packages.

Refer to the attached document for more details and additional information on the workshop.

Applications are now closed

Training materials availability: Training materials for this course are not currently available.