Version 2.4.0

Setup — metadata filters

• Sample filtering by cdesc column (e.g. QC.status)
• Row / feature filtering by rdesc column (e.g. Species)

Volcano plot (Statistics)

• Interactive volcano labeling with proteins of interest (POI) (click and search) and significant proteins (top 20/all).
• Labeled features are exported as a table

Summary tab

• Updated information such as features and samples before/after filtering.

Gene symbols & ID mapping

• Optional ID → gene symbol mapping via AnnotationDbi (human and mouse supported)

Statistics

• Differential expression summary table has been reformatted and is now exported.

Other fixes & improvements

• Export messages now only show file failures to reduce notifications
• Only the last 10 notifications will be shown to prevent notification overflow
• Fixes an issue with the multiome heatmap
• Fixes an issue with certain UI elements not rendering properly
• Fixes an issue where the exported original GCT file would contain additional columns added during the setup process

Version 2.3.2

Fixes an issue with Excel data import where, in some cases, numerical data were interpreted as strings.

Version 2.3.1

• PCA shape fill is now togglable (default no fill)
• Blank gene symbols were removed, now they are preserved as NA
• Documentation updated

Version 2.3.0

PCA Module

• Fixed PCA regression to handle datasets with <10 PCs
• PCA is now only calculated once: changes in visualizations will be comparable
• Open shapes are prioritized to improve visualization

Gene Symbol Processing

• Improves geneSymbol column formatting so that outputted gene symbols are compatible with downstream pipelines (e.g. ssGSEA, PANOPLY)
• The geneSymbol column is now always created based on a selected input column (e.g. PG.Genes)
• Improved preservation logic for existing geneSymbol columns

GCT Processing

• It is now possible to import a GCT file without a cdesc. In this case, the column names of the data matrix are saved as "Sample.ID" so that a valid cdesc exists.
• Disabled two-component normalization for datasets with >20 samples due to processing time.

Annotation Selection

• Removed filtering restrictions: all discrete columns selectable (including ID columns and <2 categories)
• Statistics tab now handles incompatibility checks with improved warnings

Statistics

• Enhanced warning messages for incompatible annotations
• Normalized values are now included in the output .csv and .GCT tables

File Format Support

• Added SSV (semicolon-separated) file support

Customization

• Fixed an issue where changing colors for an annotation other than the default annotation would not display correctly

Version 2.2.3

• Now properly handles special characters (such as "-") in annotation names during plotting and statistical analysis
• Fixes an issue where the # of categories for continuous/discrete groups was mismatched. Now, consistently, any numerical annotation with > 20 unique values will be considered continuous for analysis purposes.
• Fixes an issue where importing colors for a yaml file would cause endless notifications.

Please note git checks for macos are currently failing due to a transient GitHub error. The package is downloadable and installable on Mac OS.

Version 2.2.2

• The latest hotfix somehow caused selected colors to no longer save during customization. This is now resolved.

Version 2.2.1

• The column annotations (cdesc) were sometimes erroneously shuffled following group-wise normalization. This has now been resolved.

Version 2.2.0

• Adds a "clear all notifications" button
• Adds a color customization module that allows you to choose colors for every discrete (categorical) annotation in your dataset(s). Colors can be imported from a .yaml file either from ProTIGY or PANOPLY. Colors are automatically exported to a .yaml file in the Export tab with the other results files, or, you can export just the colors from the Customization tab.

Version 2.1.0

• Allows files to be added and removed during the setup process.
• App now automatically moves to the statistics summary tab after testing is complete.
• Implements a new hybrid contrast selection UI with matrix and list views for improved usability and scalability.
• Optimizes the two-sample T-test by processing contrasts in batches, which significantly improves performance.
• Adds helper functions for contrast selection logic, including contrast generation.
• Includes CSS styling for the new contrast selection UI components.
• Adds user documentation for the new contrast selection UI.

Version 2.0.0

First stable release of the ProTIGY R package.

Key Features

• Upload multiple GCT, CSV, TSV, or Excel files at once
• Export normalized and filtered data
• Visualize and export QC plots
• Perform statistical analysis
• Visualize all datasets simultaneously in a heatmap