Repository for the pyPheWAS project. Full documentation at https://pyphewas.readthedocs.io/en/latest/
Cailey Kerley, PhD
Shikha Chaganti, PhD
Bennett Landman, PhD
Kerley, C.I., Chaganti, S., Nguyen, T.Q. et al. pyPheWAS: A Phenome-Disease Association Tool for Electronic Medical Record Analysis. Neuroinform (2022). https://doi.org/10.1007/s12021-021-09553-4
Kerley, C.I., Nguyen T.Q., Ramadass, K, et al. pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations. JAMIA Open (2023). https://doi.org/10.1093/jamiaopen/ooad018
- Default regression equation modified to allow for both canonical and reversed PheWAS equations
- Updated plot styling to improve legibility
- Bug fix: can now run pyPhewasModel/pyProwasModel without covariates
- Other minor bug fixes
- Minor bug fixes
- pyPheWAS Explorer updates
- New demographic variables added to synthetic dataset
- convertEventToAge includes new warning for calculated ages are negative
- small bugs fixed in maximizeControls, NoveltyAnalysis, and PubMedQuery tools
- createPhenotypeFile now supports more options for controlling case/control group curation
- Documentation updates
- Novelty Analysis tools: examine the relative literary novelty of disease-phecode pairings
- pyPheWAS Explorer: an interactive visualization of PheDAS experiments
- createGenotypeFile updated - now called createPhenotypeFile
- Minor bug fixes
- Configurable threshold for number of subjects required to run the regression on an individual PheCode
- All regressions are now fit with regularization (old scheme available with 'legacy' option)
- Minor changes to Manhattan plot
- PheCode/ProCode categories added to regression file
- Minor bug fixes
- New Analysis Type: ProWAS Tools
- New Plot Type: Volcano Plot (see pyPhewasPlot)
- maximizeControls now saves explicit Case/Control matches
- New PheCode category colors in plots are more distinguishable
- Improved command line tool argument handling
- Improved error handling
- Documentation overhaul
- API update
- Minor bug fixes
- Bug fixes including FDR & Bonferroni threshold calculations
- Header saved in feature matrices
- More file formats available for saving plots
- Support for both ICD 9 and ICD 10
- All 3 regression types (binary, count, & duration) optimized for big data
- pyPhewasPipeline: a streamlined combination of pyPhewasLookup, pyPhewasModel, and pyPhewasPlot
- Compatibility with Python 3
- Age matching now saves the explicit mapping between controls/cases in addition to the resulting group file
- Operation of the ICD censoring function matches the description in the documentation
- Minor bug fixes