This is my main funded research. The aim is to investigate how early life conditions influence adult metabolic capacity and ultimately risk for type 2 diabetes. I’ll be using data from Denmark’s registers and linking to some cohort studies to apply causal structure learning methods to identify pathways between early life, adult metabolic characteristics, and diabetes. There are several sub-projects related to this main project:
- Denmark statistics application and study protocol: gitlab.com/lwjohnst/meld-protocol.
- R package development for the statistical method: NetCoupler
- An analysis of the UK Biobank and InterAct using NetCoupler to build the pipeline for the data analysis of the register datasets.
Improving data analysis and reproducibility within science
There are several projects that fall under this project heading. The main aim is to make reproducible and open science the default by making it the easiest, simplest, and fastest approach to doing science. These projects fall under (for now) three areas:
- Documentation: Create and develop a philosophy (a “manifesto”) to explicitly state how reproducible and open science should be conducted from a practical point of view. Currently being developed at
rostools/manifesto.
- R Packages: Using the manifesto as a guide, to build an ecosystem of tools that automate as many aspects of doing an open and reproducible research project and streamlining many other aspects. An example of one of these packages is the prodigenr package.
- Teaching: To integrate the ecosystem of R packages with a set of beginner-friendly and accessible training materials and documentation that future and current scientists can use to learn how to conduct reproducible and open science easily and simply. Developing and running workshops aimed at teaching researchers modern tools and skills to work openly and reproducibly. For an example of one of these projects, check out the
r-cubed teaching material.
- Other projects related to teaching include two (completed and planned) books of teaching material for Research Software Engineering in R and Python and two books of teaching material for Novice R and Python. See the main website Merely Useful for links to these books.