Features

Core Feature

This feature is available in all Portrai Explorer deployments.

Features are data columns that describe properties of each data point (cell or spot) in your dataset. Portrai Explorer uses features for color mapping, subsetting, and analysis.

Feature Types

Portrai Explorer supports two types of features:

Categorical Features

Categorical features contain discrete labels that group data points into categories.

Examples:

• Cell type (e.g., "B cell", "T cell", "Macrophage")
• Cluster assignments (e.g., "Cluster 0", "Cluster 1")
• Sample ID
• Treatment group

Characteristics:

• Finite set of distinct labels
• Each point belongs to exactly one category
• Displayed with distinct colors per category

Continuous Features

Continuous features contain numeric values that vary across data points.

Examples:

• Gene expression levels (e.g., "CD3E", "MS4A1")
• Quality metrics (e.g., "n_genes", "total_counts")
• Computed scores

Characteristics:

• Numeric values with a range (min to max)
• Displayed with a color gradient
• Can be subset by value range

Browsing Features

Sidebar Feature List

Access features through the Explorer sidebar:

1. Tab Bar - Switch between column groups (Metadata, Genes, User) and Signatures
2. Search Field - Search features by name or by note text, with a Has note checkbox inside it to show only annotated columns
3. Feature List - Scrollable list of available features
4. Detail Panel - Shows information about the selected feature

Sorting the Feature List

Use the Sort button to organize features alphabetically for easier navigation.

1. Click the Sort button (↕ icon) next to the search field
2. Choose a sorting option:

Option	Description
Default	Original order from the dataset
Name A-Z	Alphabetical order (ascending)
Name Z-A	Reverse alphabetical order (descending)

3. The feature list reorders immediately

TIP

Sorting is applied globally across every tab. It applies for the current session and resets to Default when you reload the page.

Switching Tabs

Click the tab labels to switch between the groups of columns available in this dataset:

Tab	Contents
Metadata	Observation-level columns from the dataset — cell types, clusters, quality metrics
Genes	Expression values, one column per gene
User	Columns added with Import Metadata; appears once at least one column has been imported
Signatures	Saved signatures rather than feature columns

Each tab lists categorical and continuous columns together — the icon before a column name shows which it is.

Showing All Tabs at Once

When the tabs are too wide for the sidebar, a chevron button appears at the end of the tab bar.

1. Click the chevron to unroll the tabs onto multiple rows, so every tab is visible without scrolling
2. Click it again to collapse the tabs back to a single row

The chevron only appears when the tabs actually overflow. For the feature list, the choice is remembered across sessions. While the tabs sit on one row, the strip scrolls to bring the selected tab into view.

The same control appears wherever tabs overflow in the variable and column pickers, but there it resets each time the picker is reopened.

Searching Features

Use the search field to quickly find features:

1. Click the search field at the top of the feature list
2. Type part of the feature name
3. The list filters to show matching features
4. Clear the search to show all features

The search also looks inside column notes, so a term you wrote in a note finds its column even when the column name does not contain it. A row matched that way is marked with the note icon, which is what tells you why a result you did not expect is in the list.

The count on each tab follows the search, so you can see how many matches the other tabs hold without leaving the one you are on.

Filtering to Features with Notes

The Has note checkbox sits inside the search field, at its right end. Ticking it limits the list to columns that carry a note.

• Hover it to see how many columns in the current tab have a note, before ticking it
• The filter combines with the search field: with both active, the list shows annotated columns matching your search
• It stays ticked while you switch tabs, so you can compare how many annotated columns each group holds
• The checkbox stays available when nothing is annotated. Ticking it then simply empties the list, and the list says so

This is the fastest way to answer "which of these did I annotate?" on a Genes tab holding thousands of columns.

The same search behavior and the same checkbox appear in every other column picker - the plot selectors, the subset condition editor and the signature variable picker - so a note is readable at the point where the column is used, not only here. See Everywhere a Column Is Picked.

Selecting Features

For Color Mapping

Click a feature name to apply it as the color mapping:

1. Browse or search for the desired feature
2. Click the feature name
3. The map updates to show points colored by that feature
4. The Detail Panel shows what the colors mean: each category with its color, or a histogram drawn in the color scale for a continuous feature (the map has no on-screen legend)

Previewing a Feature on Hover

Hover over a feature in the sidebar list to see an inline scatter preview of the projection shown on the map, colored by that feature, without changing the active color mapping:

1. Move the pointer over a feature row and pause briefly
2. A tooltip appears showing the projection's scatter plot colored by that feature
3. A spinner may appear for a moment before the preview renders, while a column that is not loaded yet loads (see Feature States) or, on a large dataset, while the preview is prepared

This lets you scan candidate features quickly before committing one as the map's color mapping.

The preview mirrors the map: with a lasso or a brush active, the selected points are drawn at full strength and the rest are dimmed.

If the preview cannot be prepared (for example, when the browser is short of memory), the tooltip shows Preview unavailable instead. Hover the feature again to retry.

Viewing Details

When you select a feature, the Detail Panel shows additional information:

For Categorical:

• Each category with the number of its points that pass the Subset, the cutoff and the current lasso or brush selection. Hovering a row shows its Filtered and Total counts
• Color for each category (click to customize - see Customizing Category Colors)

For Continuous:

• Minimum and maximum values
• A histogram of the values: the pale bars show every point, the colored bars the points that pass the Subset, the cutoff and the current lasso or brush selection. Hovering a bar shows its Filtered and Total counts

The counts and the histogram update shortly after a filter or selection change. Meanwhile a small spinner can briefly take a category count's place.

Hidden Features

Some features may be hidden by default (e.g., internal columns, metadata). To show hidden features:

1. Open the ... (more options) menu above the feature list
2. Enable Show Hidden Metadata to reveal hidden columns
3. The hidden columns then appear in the list alongside the others

Feature States

Features can be in different loading states:

State	Description
Idle	Not yet loaded
Loading	Currently fetching data
Ready	Fully loaded and available
Error	Failed to load

Wait for features to reach "Ready" state before using them for visualization or subsetting.

A continuous column read from the dataset, such as a gene, can go back to Idle after you stop using it: once many columns have been loaded, the least recently used ones are unloaded to free memory. Using such a column again reloads it, which can take a moment. Columns in use, such as the one coloring the map or one in a Subset condition, stay loaded.

Read-only Features

Some features are marked as read-only:

• Generated by the analysis pipeline
• Cannot be modified through the interface
• Protected from accidental changes

Read-only features can still be used for color mapping and subsetting.

Exporting Feature Data

Export feature data for use in other tools:

1. Select the feature you want to export
2. Look for an export or download option
3. Choose CSV format
4. The file downloads with point indices and values

See CSV Export for detailed export options.

Tips for Working with Features

1. Start with categorical - Begin exploration with cell type or cluster features for clear groupings
2. Use search - With many genes, search is faster than scrolling, and it reaches note text as well as names
3. Filter to your notes - The Has note checkbox in the search field pulls the handful of columns you annotated out of thousands
4. Check the Detail Panel - Its category colors or histogram show what the colors represent; read them before interpreting patterns
5. Combine with subsets - Use features both for color and subsetting simultaneously

Related Topics

• Color Mapping - Detailed color configuration
• Import Metadata - Add feature columns from a CSV file
• Column Notes - Record what a column is and how it was produced
• Facet View - Split the map by a categorical feature
• Signatures - Create custom gene groups
• Subset - Subset by feature values