Warning: Please be aware that these videos are a snapshot, and as such may use an outdated version of the tutorial and/or Galaxy. Below the video you will find links to the tutorials as they appeared at the time of recording.
Epidemiology for Bioinformaticians
Below are video tutorials for this GTN material, created for various (past) events.
Tutorial Video (July 2022)
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 own structural causal models (DAGs) using
dagitty and ggdag and then 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 BioC2021 to a
large audience of more than 100, updates that material by revising current
examples based on participant feedback as well as content updates.
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