promor 0.2.1

In previous versions, the functionality of the uniq_pep parameter (see create_df help page) was incorrectly described. We corrected the description to match its functionality as follows: “Numerical. Proteins that are identified by this number or fewer number of unique peptides are filtered out (default is 2).Only applies when input_type = "MaxQuant".

In previous versions, volcano_plot function plotted “-log₁₀(P-value)” on the y-axis by default even when sig = "adjP" and only colored the dots by their significance based on “adjP”. In this version, sig = "adjP" shows “-log₁₀.adj. P-value” on the y-axis and colors the dots by their “adjP” significance.

promor 0.2.0

A new argument (data_type) added to the create_df function to accommodate other types of LFQ data (raw intensity, iBAQ).

A new argument input_type added to the create_df function to allow users to input data from a standard quantitative matrix.

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.

naive_bayes added to the default algorithm_list argument in the train_models function.

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.