Changes in version 1.2.1.9000                      

                 Changes in version 1.2.1 (2026-04-10)                  

nestedcv and qvalue are no longer required in examples, tests, and
vignettes, in compliance with CRAN's --no-suggests check.

                 Changes in version 1.2.0 (2026-03-24)                  

Updated reference network

  - The reference network internally used by multiDEGGs is now updated
    with 28,352 additional links obtained from Omnipath. The internal
    omic_network object contains now a total of 53,035
    literature-reported biological links. Running get_diffNetworks() on
    the same data might now result in differential networks containing
    new additional links.
  - New citation added.

                 Changes in version 1.1.3 (2026-02-02)                  

Vignettes improvements.

                 Changes in version 1.1.2 (2026-01-15)                  

Patch: get_diffNetworks_singleOmic() now double checks that assayData
and metadata are aligned for the layer

                 Changes in version 1.1.1 (2025-10-24)                  

Minor fixes in documentation

                 Changes in version 1.1.0 (2025-07-29)                  

New features for feature augmentation in ML

Two new functions are provided for nested feature engineering. To use
them in combination with the nestedcv package their name must be passed
to the modifyX parameter of nestcv.glmnet() or nestcv.train().

  - The multiDEGGs_filter() function performs feature selection based
    entirely on differential network analysis.
  - The multiDEGGs_combined_filter() function combines traditional
    statistical feature selection (5 options) with differential network
    analysis.
  - Internally the two predict.multiDEGGs_filter() and
    predict.multiDEGGs_combined_filter() S3 methods generate predictions
    by creating a dataset with single and combined predictors based on
    the filtering results of a multiDEGGs_filter model.
  - The vignette has been updated to showcase the new feature

                 Changes in version 1.0.0 (2025-06-05)                  

Initial Release

  - First public version of multiDEGGs
  - Provides tools for differential network analysis.
  - Can be easily integrated in machine learning pipelines as feature
    selection method.
  - Supports both single and multi omic analyses.
  - Compatible with R >= 4.4.