Integrating Mendelian randomization and literature-mined evidence for breast cancer risk factors
Marina Vabistsevits, Tim Robinson, Ben Elsworth, Yi Liu, Tom Gaunt
This site is a navigation page for the web-based components of the article:
— Poster (IGES 2022)
— Shiny apps
— EpiGraphDB queries examples
Integrating Mendelian randomization
R/Shiny apps
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The MR effect direction heatmap app includes the results for 309 traits that were selected with filtering steps from the initial MR-EvE exploration dataset. 213 traits (or 105 after FDR correction) have evidence of an effect on at least one validation breast cancer outcome.
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Literature overlap Sankey plot app
The Sankey plot app provides a visualisation of literature spaces overlap of risk factor traits (case studies only) and breast cancer.
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MR-EvE app (legacy app)
The breast cancer MR-EvE (Mendelian Randomization “Everything-vs-Everything”) app was created to facilitate the exploration of exposures that could be breast cancer risk or protective factors. The app includes 905 exposure traits split into 12 categories, with MR results available for multiple breast cancer outcome GWAS.
EpiGraphDB queries examples
GitHub repo https://github.com/mvab/epigraphdb_mr_literature_queries provides basic examples of querying MR-EvE and literature data in EpiGraphDB. These examples may be helpful for understanding and/or replicating EpiGraphDB queries that were used in this article, or applying them to study your disease of interest.