Release History

v1.0.0 (2020-06-04)

Fixes

  • Fixed ewas_r not working for some parameter combinations
  • Improved the top_results plot to work with non-continuous values (which don’t have Betas)
  • Corrected ewas results for some scenarios (strata and clusters) related to missing data (incorrect degrees of freedom)

Tests

  • Added additional analysis tests with realistic data (more missing values)
  • All analysis tests are now passing with 1E-4 relative tolerance
  • Added the first plot tests

v0.10.0 (2020-05-28)

Enhancements

  • Manhattan plot split into three functions (raw, bonferroni, and fdr) and now has a custom threshold parameter
  • Use Pandas v1.0+
  • Refactored regression objects to simplify internal code and potentially allow for more types of regression in the future
  • Added an ewas_r function that seamlessly runs the ewas analysis in R, using the R survey library * This is recommended when using weights, as the python version has some inconsistencies in some edge cases
  • Added a skewness function
  • Added a top_results plot
  • Add a drop_unweighted parameter to the SurveyDesignSpec to provide an easy (if potentially incorrect) workaround for observations with missing weights

Fixes

  • Provide a warning and a convenience function when categorical types have categories with no occurrences
  • Catch errors when categorizing variables with many unique string values
  • Corrected some edge-case EWAS results when using weights in the presence of missing values
  • Avoid some cryptic errors by ensuring the input to some functions is a DataFrame and not a Series

Tests

Many additional tests were added, especially related to EWAS

v0.9.1 (2019-11-20)

Minor documentation update

v0.9.0 (2019-10-31)

Enhancements

  • Add a figure parameter to histogram and manhattan plots in order to plot to an existing figure
  • SurveyDesignSpec can now utilize more parameters, such as fpc
  • The larger (numeric or alphabetic) binary variable is always treated as the success case for binary phenotypes
  • Improved logging during EWAS, including printing the survey design information
  • Extensively updated documentation
  • CLARITE now has a logo!

Fixes

  • Corrected an indexing error that sometimes occurred when removing rows with missing weights
  • Improve precision in EWAS results for weighted analyses by using sf instead of 1-cdf
  • Change some column names in the EWAS output to be more clear

Tests

An R script and the output of that script is now included. The R output is compared to the python output in the test suite in order to ensure analysis result concordance between R and Python for several analysis scenarios.

v0.8.0 (2019-09-03)

Enhancements

  • Allow file input in the command line for skip/only
  • Make the manhattan plot function less restrictive of the data passed into it
  • Use skip/only in the transform function

Fixes

  • Categorization would silently fail if there was only one variable of a given type

v0.7.0 (2019-07-23)

Enhancements

  • Improvements to the CLI and printed log messages.
  • The functions from the ‘Process’ module were put into the ‘Modify’ module.
  • Datasets are no longer split apart when categorizing.

v0.6.0 (2019-07-11)

Extensive changes in organization, but limited new functionality (not counting the CLI).

v0.5.0 (2019-06-28)

Enhancements

Fixes

  • Add some validation of input DataFrames to prevent some errors in calculations

Tests

  • Added an initial batch of tests

v0.4.0 (2019-06-18)

Support EWAS with binary outcomes. Additional handling of NA values in covariates and the phenotype. Add a ‘min_n’ parameter to the ewas function to require a minimum number of observations after removing incomplete cases. Add additional functions including ‘plot_distributions’, ‘merge_variables’, ‘get_correlations’, ‘get_freq_table’, and ‘get_percent_na’

v0.3.0 (2019-05-31)

Add support for complex survey designs

v0.2.1 (2019-05-02)

Added documentation for existing functions

v0.2.0 (2019-04-30)

First functional version. Mutliple methods are available under a ‘clarite’ Pandas accessor.

v0.1.0 (2019-04-23)

Initial Release