Course Overview
The “Introduction to Biostatistics for Genome Wide Association testing” workshop provides an introduction to the basic concepts in biostatistics required for genome wide association studies, e.g. data types, experimental design, statistical tests, probabilities, R, etc. During the second week, basic statistical concepts relevant to population genetics and genome wide association tests will be introduced to build foundational knowledge for genome wide association studies. The workshop will consist of a series of theory and lectures during the morning sessions and “hands on” practical lab sessions during the afternoon periods.
The “Introduction to Biostatistics for Genome Wide Association testing” workshop provides an introduction to the basic concepts in biostatistics required for genome wide association studies, e.g. data types, experimental design, statistical tests, probabilities, R, etc. During the second week, basic statistical concepts relevant to population genetics and genome wide association tests will be introduced to build foundational knowledge for genome wide association studies. The workshop will consist of a series of theory and lectures during the morning sessions and “hands on” practical lab sessions during the afternoon periods.
Intended Audience
This workshop is aimed at H3Africa project members who will be involved in the design and analyses of population data and genome wide association testing, and those who need statistical skills for their research.
This workshop is aimed at H3Africa project members who will be involved in the design and analyses of population data and genome wide association testing, and those who need statistical skills for their research.
Keywords: Genetics, Genomics, Biostatistics
Skill level of training:
Beginner
Language: English
Credential awarded: No credential awarded
Type of training: Blended/hybrid learning
Venue of the course:
Dates for the course:
Every Tuesday and Thursday from 10:30 CAT to 14:30 CAT
Course organisers: Dr. Jean-Baka Domelevo Entfellner, Prof. Ahmed Rebai, Dr Najla Kharrat, Dr Amel Ghouila, Dr Kais Ghedira, Prof. Alia Benkahla, Mohamed Alibi
Participation:
Course Sponsors: H3ABioNet and the Institut Pasteur de Tunis H3ABioNet Node
Course objectives
After this workshop participants should be able to:
- Determine which statistical tests are appropriate given their data types
- Conduct hypothesis testing and correct for multiple hypothesis testing
- Determine what types of sampling there are and the effective sample size required
- Have a good familiarity with R and conducting statistical tests within R
- Have a good background on the theory behind population genetics
- Be able to conduct a variety of population genetics statistical tests
Classroom applications
Registration for classrooms opens:
Thu, 01/01/1970
Registration for classrooms closes:
Thu, 01/01/1970
Notification date for successful classrooms:
Thu, 01/01/1970
Maximum number of participants that may be accepted per classroom will be
capped at
Participant applications
Registration for participants opens:
Thu, 01/01/1970
Registration for participants closes:
Thu, 01/01/1970
Participant registration link:
Syllabus and Tools
Participants will learn about Biostatistics and R, population genetics
Prerequisites
Participants will need to work through the following resources to enable them to gain the most from the workshop:
http://www.ee.surrey.ac.uk/Teaching/Unix/
http://www.r-tutor.com/r-introduction
Course limitations
This workshop will only provide a foundation for continued learning in biostatistics and population genetics and will not make you an expert in biostatistics, population genetics and genome wide association testing and studies.
This workshop will only provide a foundation for continued learning in biostatistics and population genetics and will not make you an expert in biostatistics, population genetics and genome wide association testing and studies.
For more information, please visit
Training material availability
Training materials for this course are available as a single downloadable archive here: https://doi.org/10.25375/uct.19105583. Should you re-use any of these materials, please ensure that both the author/s of the material AND H3ABioNet are clearly credited.
