Documentation : Variant Filtering

1. General

It is advised to read the following two sections before starting to browse variants.

2. Selecting Filters

Go to Variant Filter in the top menu:

  1. Select a sample by either starting to type the sample name, or by switching to the selection list. Alternatively, provide a genomic region or Gene Symbol
  2. After selecting the sample, a link to load the VCF/BAM data (if available) into IGV will be shown on the right.

  3. Select the 'Filter Settings' tab
  4. Select Filter rules by pressing the green plus icons () for the relevant category.
  5. For the newly added rule in the table, select all mandatory options.
    1. Match/NotMatch : Include/Exclude variants based on this rule
    2. First selection box: filtering is based on this item
    3. Additional fields: used to refine the filter
    4. Note the following:
      • Selecting multiple entries in a single selection box (eg nonsense+stop_gain) means that either of both should be matched.
      • Creating multiple rules with one entry each (eg rule for nonsense + rule for stop_gain) means that both rules should be matched.
    5. Save Filter settings for future usage using the 'Save Current Filter' button, and provide a meaningfull name.
    6. VariantDB uses cookies to save your settings for a while. If you close the browser and come back later, your filters will be restored

    3. Selecting Annotations

    1. Select the 'Annotations' tab
    2. Select the needed annotatons by clicking the checkboxes.
    3. Sets of annotations can be saved by using the 'Save Current Annotations' button.

    4. Apply the filter and get annotations

    Click the 'execute' button to get the results. Results are presented in batches of 100 matching variants. On the 'export' tab, the button will start the generation and download of a csv file with all matching variants.

    5. Export

    Under the export tab, you can obtain a CSV file for further downstream annotation. It will contain all selected annotations for the filtered data.

    6. Example Filtering Strategies

    See here