## promor 0.2.0

CRAN release: 2023-01-17

##### New data types allowed
• A new argument (data_type) added to the create_df function to accommodate other types of LFQ data (raw intensity, iBAQ).
##### A new input type added
• A new argument input_type added to the create_df function to allow users to input data from a standard quantitative matrix.
##### Workflow changes
• To allow for missing data imputation prior to or after data normalization step (depending on the imputation method used), the following changes were made:
• norm_df and imp_df arguments replaced with a generic df argument in the functions, find_dep, impute_na, normalize_data, and heatmap_de
• A note was added to the tutorials to clarify that for some imputation methods, such as the kNN method, data normalization should be performed prior to imputation.
##### Default machine learning algorithms
• naive_bayes added to the default algorithm_list argument in the train_models function.

## promor 0.1.1

CRAN release: 2022-11-01

##### Bug fixes
• Fixes a minor issue with create_df when removing potential contaminants. The number of potential contaminants removed is now shown in the console.
• Fixes an issue with find_dep that previously used a fixed value for the adj_method argument.
• Fixes an issue with the file_path argument for saving the “TopHits.txt” file produced by the find_dep function.
##### Other changes
• Citation file updated with the biorxiv preprint details.
• Readme file updated with information on the Shiny App.
• Help pages updated.

## promor 0.1.0

CRAN release: 2022-07-20

• First official release!