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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.
Venue of course: Online through 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
Registration for participants opens: 4th April 2022
Registration for participants closes: 24th April 2022
Notification date for successful Applicants: 6th June 2022
Link to participant application form: Click here
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:
Date |
Session 1 10:00-11:00am CAT |
Session 2 11:00-12:00am CAT |
Session 3 12:00-1:00pm CAT |
Interactive hour with Instructor/s (1:00-2:00PM CAT) |
Monday 27 June 2022 |
Module1: Lecture |
Module 2: L1 |
Module 2: L2 |
Faisal; Katherine & Verena |
Tuesday 28 June 2022 |
Module 3: Lecture |
Module 4: L1 |
Module 4: L2 |
Lyndon & Verena; Ayton and Ziyaad |
Wednesday 29 June 2022 |
Module 5: Lecture |
Module 5: FAIR Tutorial |
Melek & Ziyaad |
|
Thursday 30 June 2022 |
Module 6: Lecture |
Module 6: DMP Tutorial - Group A |
Module 6: DMP Tutorial - Group B |
Faisal; Ayton |
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.
Objectives: After this RDM short course participants should be able to:
Course limitations: This course will only provide a foundation for continued learning in research data management and will not teach any advanced RDM aspects.
Course Overview/description:
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/Description: There will be two courses offered by the BioConductor community:
Introduction to Bioconductor Annotation Resources (Thursday, 29th April 2021 @ 8am EDT/12noon GMT/1pm WAT/ 2pm CAT/3pm EAT to 11am EDT/3pm GMT/ 4pm WAT/5pm CAT/6pm EAT) (https://jmacdon.github.io/Bioc2020Anno/#introduction-to-bioconductor-annotation-resources)
There are various annotation packages provided by the Bioconductor project that can be used to incorporate additional information to results from high-throughput experiments. This can be as simple as mapping Ensembl IDs to corresponding HUGO gene symbols, to much more complex queries involving multiple data sources. In this workshop, we will cover the various classes of annotation packages, what they contain, and how to use them efficiently.
Epidemiology for Bioinformaticians (Friday, 30th April 2021 – 8am EDT/12noon GMT/1pm WAT/ 2pm CAT/3pm EAT to 11am EDT/3pm GMT/ 4pm WAT/5pm CAT/6pm EAT ) (https://chloemirzayi.com/EpiForBioWorkshop2020/#epidemiology-for-bioinformaticians) Concepts of causal inference in epidemiology have important ramifications for studies across bioinformatics and other fields of health research. In this workshop, we introduce basic concepts of epidemiology, study design, and causal inference for bioinformaticians. Emphasis is placed on addressing bias and confounding as common threats to assessing a causal pathway in a variety of study design types and when using common forms of analyses such as GWAS and survival analysis. Workshop participants will have the opportunity to create their structural causal models (DAGs) and use this model to determine how to assess an estimated causal effect. Examples using DESeq2, edgeR, and limma will be used to show how multivariable models can be fitted depending on the hypothesized causal relationship.
Presented successfully at BioC2019 to 30 people, updates that material by adding a brief demonstration of ggdag, revised conceptual emphasis based on participant feedback, and applied examples using data from curated metagenomic data.
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. 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 proposed courses will lay a foundation on how to efficiently use open-source Bioconductor resources for bioinformatics analysis. The course will be in two main forms which include;
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
You may now register for the upcoming virtual introduction to hands-on Bioconductor Workshop organized in collaboration with H3Africa, H3ABioNet, and the Bioconductor Community happening from 29-30 April 2021.
This workshop/course is FREE to register and attend and promises to be interesting and beneficial.
Refer to the attached document for more details and additional information on the workshop.
Follow link to register: https://htraindb.h3abionet.org/node/2935
Registration closes: 22nd April 2021
Course Overview
The Research Data Management (RDM) short course will introduce the principles and practices of RDM and provide practical advice for implementing these practices in an African research context. Topics covered will 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 Data Management Plan.
Intended Audience
The course is aimed at graduate students and biomedical scientists who are currently working on clinical genomics and bioinformatics projects in Africa.
Logistics
Venue of course: Online through Zoom.
Dates for the course: 22-25 June 2021; from 10:00 CAT to 14:00 CAT.
Course organisers: 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
Participant applications
Registration for participants opens: 4th May 2021
Registration for participants closes: 24th May 2021
Notification date for successful Applicants: 31st May 2021
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.
Objectives: After this RDM short course participants should be able to:
Course limitations: This course will only provide a foundation for continued learning in research data management and will not teach any advanced RDM aspects.
Course Curriculum
Course Schedule
Date |
Session 1 (45 minutes) |
Session 2 (45 minutes) |
Session 3 (45 minutes) |
Interactive hour with Instructor/s (1:00-2:00PM CAT) |
Tuesday 22 June 2021 |
Module1: Lecture |
Module 2: L1 |
Module 2: L2 |
Faisal; Katherine & Verena |
Wednesday 23 June 2021 |
Module 3: Lecture |
Module 4: L1 |
Module 4: L2 |
Lyndon; Ayton & Ziyaad |
Thursday 24 June 2021 |
Module 5: Lecture |
Module 5: FAIR Tutorial |
Melek & Ziyaad |
|
Friday 25 June 2021 |
Module 6: Lecture |
Module 6: DMP Tutorial |
Faisal |
Course Overview/description:
Next generation sequencing (NGS) has become an essential tool in genetic and genomic analysis. It is increasingly important for experimental scientists to gain the bioinformatics skills required to analyse the large volumes of data produced by next generation sequencers. This course will equip participants with the essential informatics skills required to begin analysing NGS data and apply some of the most commonly used tools and resources for sequence data analysis.
The programme will cover prominent sequencing technologies, algorithmic theory and principles of bioinformatics, with a strong focus on practical computational sessions using sequence analysis techniques and tools applicable to any species or genome size. A variety of applications will be covered from post-sequencing analysis - QC, alignment, assembly, variant calling and RNA-Seq.
This course will apply a blended learning format consisting of locally coordinated classrooms referred to as “remote classrooms”. Click here for more information. Please note: Due to the COVID-19 pandemic, the local classrooms will run virtually, using Zoom and downloadable virtual machines.
Applications close 22 February 2021
Intended Audience:
Applicants should be postdoctoral scientists, senior PhD students, junior faculty members or clinicians/healthcare professionals actively engaged in or soon to commence research involving next generation sequencing data analysis.
Priority will be given to applicants who 1) currently or will soon have NGS experimental data to analyse 2) will utilise the bioinformatics techniques taught in at least two of the modules/topic areas listed in the programme outline in their experiments 3) have a clear plan/opportunity to disseminate the knowledge amongst their peers. We encourage applicants to highlight these areas in their application.
Learning objectives/outcomes: After this workshop participants should be able to:
• Use the unix command-line as a tool for data analysis
• Describe the different NGS data file formats available
• Perform QC assessment of high throughput sequencing data
• Explain the algorithmic concepts behind read alignment, variant calling and structural variant detection
• Perform read alignment, variant calling and structural variation detection using standard tools
• Analyse RNA-Seq and CHiP-seq data
• Perform a genome assembly using NGS data
Prerequisites:
The practical sessions will be taught exclusively through Unix/Linux. Therefore, participants are required to have some previous experience using the Linux operating system. This will be essential for participants to fully benefit from the course. There are numerous online introductory tutorials to the UNIX/Linux operating system and command line, including:
Syllabus and Tools:
The course will cover the following topics:
• Intro to Unix/Linux & running workflows
• Introduction to NGS Technologies
• NGS data pre-processing and QC
• Alignment to reference sequences
• Variant calling and annotation
• ChipSeq
• RNASeq
• Genome assembly
Dates for the workshop:
Tuesdays & Thursdays from 13/04/2021 until 10/06/2021
Classroom registration opens:
04/12/2020
Classroom registration closes:
07/01/2021
Notification date:
14/01/2021
Participant application:
Applications are now open, please apply here. Applications close 22 February 2020 at 11:59 pm CAT. Successful applicants will be informed during the first two weeks of March.
Workshop organisers:
WGC ACSC and H3Abionet
Workshop Sponsors:
Wellcome Genome Campus Advanced Courses & Scientific Conferences - H3Abionet
Keywords:
NGS, Data analysis
Skill level of training:
Advanced
Language:
English
Credential awarded:
Workshop certificate
Type of training:
Virtual
Workshop limitations:
The course aims to provide a hands-on introduction to bioinformatics for next generation sequencing, and should not be considered a complete education in the theoretical and mathematical foundations of the topics.
Workshop Programme:
The workshop will run for 8 weeks, on Tuesdays and Thursdays from the 13th of April until the 10th of June.
Tools and Services
Resources
Communication