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06 Filter Data
This tab allows users to filter their dataset to include only the samples and features of interest. Filtering is optional and depends on the goals of your analysis.
Dynamically generated controls for every sample-level variable (colData) in your experiment:
- Numeric variables → range sliders
- Categorical variables → multi-select pickers with live search
Select the values you want to keep. Samples not matching your selection will be excluded from all downstream analyses.
Dynamically generated controls for every feature-level variable (rowData) in the currently selected assay (as set by the Aggregation Level header). Works the same way as the sample filters: numeric variables get sliders, categorical variables get pickers.
Feature filters apply independently per assay. To filter a different assay's features, change the Aggregation Level in the header.
After setting your filters, a summary shows:
- Number of samples remaining after filtering
- Number of features retained
Use this to confirm your filters are working as intended before moving to analysis.
- Apply Filters: Commits the current filter selections and updates all downstream tabs.
- Clear All Filters: Resets all filters and restores the full dataset.
Data processing (log transformation, imputation, normalization) is configured separately via the Advanced Settings popover in the header. See the Advanced Settings page for details.