proBatch  v1.99.0
==============
Changes:
* Added support for extended QFeatures object - `ProBatchFeatures` - as input data format. 
  All functions that previously accepted `data_matrix` and `df_long` formats, 
  now also accept `ProBatchFeatures` objects. 
* Added support for multiple assays in `ProBatchFeatures` objects. All functions that
  previously accepted only a single data matrix, now also accept multiple data
  matrices stored in different assays of a `ProBatchFeatures` object, inluding plotting functions: `plot_heatmap_diagnostic`, `plot_pca`, `plot_sample_mean`, `plot_boxplot`.
* Added support for multiple features in `ProBatchFeatures` objects. 
* Added limma-based batch correction method (`removeBatchEffect`) for `ProBatchFeatures` objects.
* Added new visualization functions to plot missing value patterns in `ProBatchFeatures` objects:
  - `plot_NA_heatmap()`
  - `plot_NA_density()`
  - `plot_NA_frequency()`

proBatch  v1.1.0
==============

Changes:
* all functions that deal with data matrix and sample annotation, are checking 
for sample consistency (discrepancies in sample IDs);
* all functions, transforming the data (log, normalization, batch correction) 
work with both `data_matrix` and `df_long` formats, and called as 
`[correction_func]_dm` and `[correction_func]_df` correspondingly.
* for all `df_long` functions, modifying `measure_col` (Intensity), keeping the 
old column as:
    - log_transform_df: beforeLog_[measure_col];
    - normalization: preNorm_[measure_col];
    - batch correction: preBatchCorr_[measure_col];
    - (if adjusting trend): preTrendFit_[measure_col].
  Note that this increases the data size. If this is of a concern, 
  use `data_matrix` format instead.
* renamed functions: 
  - "center_peptide_batch_medians" to "center_feature_batch_medians"
  - "normalize_custom_fit" into "adjust_batch_trend";
* harmonised arguments in plotting functions, all of them now take sample annotation and color_list/color_scheme.
* simplified color scheme definition and usage, which is now consistent over all plotting functions (check updated argument definitions!)
* Added internal automated definition of color scheme (useful when single plotting functions are used, and color scheme consistency is not critical);
* consistent handling of missing values by proteome-wide diagnostic functions;
* renamed "plot_heatmap" into "plot_heatmap_diagnostic" as now "plot_heatmap_generic" is added for non-standard cases of heatmap plotting;
* better legend for DateTime color mapping in meanplots, boxplots and feature-level plots.