-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. +The PanelApp tracks show regions that are related to human disorders. These can be either +genes, short tandem repeats or copy number variants. The regions were curated by groups of +specialists collaborating using the PanelApp web tool. The primary website is Genomics England PanelApp. +Another deployment of the website, with different data, is +PanelApp Australia. +
+ ++Originally, PanelApp was developed to aid interpretation of participant genomes in the + +100,000 Genomes Project, +Genomics England PanelApp now being used as the platform for +achieving consensus on gene panels in the NHS + Genomic Medicine Service (GMS). Later, the same platform was also deployed by +Australian + Genomics. +
+Genes and genomic -entities (short tandem repeats/STRs and copy number variants/CNVs) +entities, so 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: -
+There are six subtracks in total: Three different types (genes, STRs and CNVs) and these +three exist for both countries, England and Australia. The three types of tracks are:NOTE: Due to a bug in the PanelApp gene API, between 5 and 20% of gene entries are missing as of 11/2/22.
The individual tracks are colored by confidence level:
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.
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 genes.bb, tandRep.bb and cnv.bb. 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 http://hgdownload.soe.ucsc.edu/gbdb/$db/panelApp/genes.bb -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. +Genomics England PanelApp API +and the Australia PanelApp API.
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. +coordination and consultation, and Zornitza Stark from Australia PanelApp. +Thanks to Beagan Nguy, Lou Nassar, 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