PanelApp Track Settings
Genomics England PanelApp Diagnostics   (All Phenotype and Literature tracks)

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Filter by Confidence Level (select multiple items - help)
Label: hgnc Symbol   

Display data as a density graph:
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 PanelApp CNVs  Genomics England PanelApp CNV Regions   Data format 
 PanelApp Genes  Genomics England PanelApp Genes   Data format 
 PanelApp STRs  Genomics England PanelApp Short Tandem Repeats   Data format 
Assembly: Human Dec. 2013 (GRCh38/hg38)


The Genomics England PanelApp tracks show gene panels that are related to human disorders. Originally developed to aid interpretation of participant genomes in the 100,000 Genomes Project, PanelApp is now also being used as the platform for achieving consensus on gene panels in the NHS Genomic Medicine Service (GMS). As panels in PanelApp are publicly available, they can also be used by other groups and projects. Panels are maintained and updated by Genomics England curators.

Genes and genomic entities (short tandem repeats/STRs and copy number variants/CNVs) have been reviewed by experts to enable a community consensus to be reached on which genes and genomic entities should appear on a diagnostics grade panel for each disorder. A rating system (confidence level 0 - 3) is used to classify the level of evidence supporting association with phenotypes covered by the gene panel in question.

The available data tracks are:

  • Genomics England PanelApp Genes (PanelApp Genes):
    shows genes with evidence supporting a gene-disease relationship.

    NOTE: Due to a bug in the PanelApp gene API, between 5 and 20% of gene entries are missing as of 11/2/22.

  • Genomics England PanelApp STRs (PanelApp STRs):
    shows short tandem repeats that can be disease-causing when a particular number of repeats is present.

  • Only on hg38: Genomics England PanelApp Regions (PanelApp CNV Regions):
    shows copy-number variants (region-loss and region-gain) with evidence supporting a gene-disease relationship.

Display Conventions

The individual tracks are colored by confidence level:

  • Score 3 (lime green) - High level of evidence for this gene-disease association. Demonstrates confidence that this gene should be used for genome interpretation.
  • Score 2 (amber) - Moderate evidence for this gene-disease association. This gene should not be used for genomic interpretation.
  • Score 0 or 1 (red) - Not enough evidence for this gene-disease association. This gene should not be used for genomic interpretation.

Mouseover on items shows the gene name, panel associated, mode of inheritance (if known), phenotypes related to the gene, and confidence level. Tracks can be filtered according to the confidence level of disease association evidence. For more information on the use of this data, see the PanelApp FAQs.

Data Access

The raw data can be explored interactively with the Table Browser or the Data Integrator. For automated analysis, the data may be queried from our REST API.

For automated download and analysis, the genome annotation is stored in a bigBed file that can be downloaded from our download server. The files for this track are called, and Individual regions or the whole genome annotation can be obtained using our tool bigBedToBed which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found here. The tool can also be used to obtain only features within a given range, e.g. bigBedToBed -chrom=chr21 -start=0 -end=100000000 stdout

Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.

Data is also freely available on the PanelApp API.

Updates and archiving of old releases

This track is updated automatically every week. If you need to access older releases of the data, you can download them from our archive directory on the download server. To load them into the browser, select a week on the archive directory, copy the link to a file, go to My Data > Custom Tracks, click "Add custom track", paste the link into the box and click "Submit".


PanelApp files were reformatted at UCSC to the bigBed format. The script that updates the track is called updatePanelApp and can be found in our Github repository.


Thank you to Genomics England PanelApp, especially Catherine Snow for technical coordination and consultation. Thank you to Beagan Nguy, Christopher Lee, Daniel Schmelter, Ana Benet-Pagès and Maximilian Haeussler of the Genome Browser team for the creation of the tracks.


Martin AR, Williams E, Foulger RE, Leigh S, Daugherty LC, Niblock O, Leong IUS, Smith KR, Gerasimenko O, Haraldsdottir E et al. PanelApp crowdsources expert knowledge to establish consensus diagnostic gene panels. Nat Genet. 2019 Nov;51(11):1560-1565. PMID: 31676867