Genomics England PanelApp

A crowdsourcing tool to allow gene panels to be shared, downloaded, viewed and evaluated by the Scientific Community

Are you using PanelApp in your genome analysis/research? Let us know and help us promote the value of this resource: panelapp@genomicsengland.co.uk

PanelApp Release (V2.0)

What's New?

Background

What is PanelApp?

Genomics England PanelApp is a publically-available knowledgebase that allows virtual gene panels related to human disorders to be created, stored and queried. It includes a crowdsourcing tool that allows genes to be added or reviewed by experts throughout the worldwide scientific community, providing an opportunity for the standardisation of gene panels, and a consensus on which genes have sufficient evidence for disease association.

The diagnostic grade ‘Green’ genes and their modes of inheritance in the PanelApp virtual gene panels are used to direct the variant tiering process for the interpretation of genomes in the 100,000 Genomes Project. As panels in PanelApp are publically available, they can also be utilised by others.

How Gene Panels are Defined

For the 100,000 Genomes Project, gene panels are mapped to one or more recruitment categories, indicated by the gene panel name (Level 4 Title) and/or listed under ‘relevant disorders’ for each panel in PanelApp. Gene panels are created in a number of steps for Rare Diseases:

  1. An initial gene list is drawn up from established sources (UKGTN, Radboud UMC, Emory Genetic Laboratory and Illumina) and from disease area experts. The initial gene panel created is Version 0.

  2. Expert review of each gene is crowdsourced.

  3. Evaluation of the reviews, further curation and consultation with the Genomics England clinical team results in a finalised panel. The panel will then be promoted to Version 1 and used in the interpretation of participant genomes.

Note that PanelApp gene panels are not used in interpretation until initial expert review and curation has been completed and the panel has been promoted to ‘Version 1’. Before this, panels are viewable and can be reviewed but the rating of genes has not been finalised.

Understanding Gene Ratings on a Version 1+ Gene Panel

Figure 1

Figure 1: A traffic-light system is used to rate genes on a Version 1+ gene panel.

We classify genes on a panel according to a traffic light system (Figure 1). Genes are rated in terms of the level of evidence to support their association with the phenotypes covered by the gene panel in question. The criteria for assessing the evidence were developed from a combination of the ClinGen DEFINITIVE and DDG2P CONFIRMED gene evidence levels and can be viewed on the Guidelines tab.

A diagnostic-grade (Green) rating on a Version 1+ panel requires evidence from 3 or more unrelated families or from 2-3 unrelated families where there is strong additional functional data. Genes that do not meet these criteria are rated as Amber (borderline) or Red (low level of evidence) and are not used in Tiering.

How Do I Add Genes and Reviews to a Gene Panel?

PanelApp has more than 500 registered reviewers from 25 countries, the majority of whom are experts in rare disease diagnosis from the UK. We encourage experts to contribute their knowledge to update existing panels and help create new diagnostic-grade panels - please register here

Uses and Users of PanelApp

The diagnostic grade ‘Green’ genes and their modes of inheritance on the Version 1+ PanelApp virtual gene panels are used to direct the Genomics England Rare Disease Tiering process. This Tiering process is to aid NHS Genomics Medicine Centre (GMC) evaluation of Rare Disease primary finding results by annotating variants that are plausibly pathogenic based on their segregation in the family, frequency in control populations, effect on protein coding, mode of inheritance and whether they are in a Green gene in the virtual gene panel(s) applied to the family. Variants in diagnostic grade ‘Green’ genes can be tiered as Tier 1 or Tier 2.

Gene panels in PanelApp can also be utilised for other projects, clinics and databases:

I am a Clinician or other Healthcare Professional…

You could use PanelApp to:

• View and interpret a panel that has been applied to your patient

• Look at the evidence for inclusion of a gene(s) in your patient report during a MDT

• Review gene(s) on panel(s) for disease(s) matching your expertise

• Add diagnostic genes missing from a panel

• Add your publications as evidence for gene-disease relationships

• Suggest additional panels to be added that would be useful for research or the clinical community (contact panelapp@genomicsengland.co.uk)

• Provide input on whether gene panels should be combined/merged (contact panelapp@genomicsengland.co.uk)

I am a Researcher…

You could use PanelApp to:

• Source data for hypothesis generation.

• Study gene-disease relationships for genome interpretation, pathway analysis and more.

• Use ‘tagged’ genes to investigate genes with interesting disease-causing mechanisms.

• Use Red and Amber genes as a source of genes needing further evidence/investigation within your disease of interest for certain diseases.

• Review genes and/or panels you have expertise in to help genome interpretation.

• Add novel genes to panels that you find within your research.

• Add your publications as evidence for gene-disease relationships.

• Suggest additional panels to be added that would be useful for research or the clinical community (contact panelapp@genomicsengland.co.uk)

• Provide input on whether gene panels should be combined/merged (contact panelapp@genomicsengland.co.uk)

• Query PanelApp data through WebServices.

I am a Bioinformatician

You could use PanelApp to:

• Use panels for your exome/genome interpretation pipeline.

• Query PanelApp data through WebServices.

This is interim information and has not yet received final approval from Genomics England internal governance processes or NHS England and is therefore potentially subject to change.

Acknowledgements

Thank you to all reviewers and those who have contributed feedback to help the development of PanelApp. Please see individual panels for the name and affiliation of contributing reviewers.

Thank you to all experts who contributed gene lists during the development of rare disease eligibility statements and data models, or by submitting their own gene panels. These have been added to the gene panels on PanelApp where possible.

PanelApp creator:

Antonio Rueda-Martin

PanelApp Developer: Oleg Gerasimenko

Software developer:

Paul Hayes

Current PanelApp Curators:

Ellen McDonagh, Sarah Leigh, Rebecca Foulger, Olivia Niblock, Louise Daugherty, Arianna Tucci, Helen Brittain.

Previous PanelApp Curators:

Eik Haraldsdottir, Ellen Thomas, Caroline Wright, Emma Baple, Damian Smedley, Chris Boustred, Kirsty McCaffrey, Alice Gardham, Richard Scott, Chris Campbell.

Other contributers to the PanelApp and PanelApp documentation:

Augusto Rendon, Katherine Smith, Clare Turnbull, Jo Whittaker, Mina Ryten, Emma Baple, Tom Fowler, Genomics England Platform Team & Service Desk

V&F GeCIP Working Group Members

This is interim information and has not yet received final approval from Genomics England internal governance processes or NHS England and is therefore potentially subject to change.

Disclaimer

PanelApp Uses Exclusions of Liability

PanelApp gene lists are provided by Genomics England in good faith, and for the benefit of the research community. The original gene lists have been supplied through commercial and academic providers, but have not been separately verified by Genomics England. Equally, expert reviewers and curators adding content and comments through PanelApp do so under their own responsibility and without verification by Genomics England. Users must themselves verify the accuracy and content any information (including in respect of ownership of any intellectual property rights) obtained through PanelApp in advance of its use for any purpose. Genomics England, any expert reviewers and curators hereby exclude any and all liability, including without limitation under any laws of contract, tort (including negligence) or statutory duty or otherwise, and do not accept any liability or responsibility for uses made of the PanelApp gene lists or comments by individual reviewers.

PanelApp Connections Exclusions of Liability

Access to the PanelApp is not guaranteed. Genomics England accepts no liability and excludes all liability in respect of interruptions in accessing or inability to access the PanelApp gene lists at any time. Persons accessing PanelApp are responsible keep their anti-virus and security software up to date. Genomics England consequently accepts no liability for any loss or damage occurring as a result of any person using or connecting to or through PanelApp.

General Exclusion of Liability and Limitations on exclusions of Liability

Genomics England shall not be responsible for any of the following losses to persons using or accessing PanelApp, howsoever incurred, whether in contract, tort (including negligence), breach of statutory duty or otherwise: indirect losses, consequential losses, loss of income or revenue, loss of profit, third party claims, loss of business, loss of data, loss of anticipated savings, or any loss of opportunity.

No provision of this disclaimer shall operate to limit or exclude liabilities which cannot by the applicable laws of England be so limited or excluded.

News & Notifications

Follow @GenomicsEngland #PanelApp on Twitter

View and filter updates to PanelApp on the Activity page

02.02.2018 Amelogenesis Imperfecta panel promoted to version 1

Thank you to the reviewers for making this possible.

23.01.2018 Congratulations to our new Curator Eleanor Williams who has been awarded this year's Biocuration Society Career Award!

We are happy to announce that Eleanor has just joined the Genomics England PanelApp Curation Team, bringing a wealth of Biocuration experience. Read more about her career and her valuable work that has led to this award.

18.01.2018 PanelApp presented at the Pan Arab Human Genetics Conference 2018

A talk entitled "The 100,000 Genomes Project Rare Disease Programme: Achievements and Future Plans" was presented by Dr Emma Baple, Clinical Lead for Rare Disease Validation and Feedback at Genomics England. Her talk included how PanelApp is used for genome analysis and diagnosis of rare diseases. On PanelApp we now have over 800 registered reviewers from around the world - including those from Arab countries.

05.01.2018 Intellectual disability gene panel update Phase II

The following major updates were made to the ID gene panel:

  • Reviews for 290 genes by Genomics England Curators and Clinical Team were added.
  • Gene status for these genes was updated according to evidence level, resulting in 41 new Green genes (858 in total).
  • The number of total genes on the panel was increased from 1895 to 1911.
  • Updated version: 1.625 (previous version before updates began was 1.561).

03.01.2018 EDS Society news post regarding PanelApp

Read this blog post regarding our EDS gene panel, reviewed by members of the EDS Society.

PanelApp holiday closure Friday 22nd December 2017 to 2nd January 2018

Dear PanelApp Users - please note that Genomics England offices will be closed from Friday 22nd December 2017 until 2nd January 2018, and so there may be a delay in response to registration requests or emails to panelapp@genomicsengland.co.uk - PanelApp will still be available during this time for you to review, download or query panels. We would like to thank all our Reviewers and wish a happy holiday to all our Users

15.12.2017 Primary Membranoproliferative Glomerulonephritis promoted

The PMG panel was promoted to Version 1 - the green genes on this panel can now be used for genome interpretation - thank you to Dr Daniel Gale, University College London, Arianna Tucci (Genomics England Clinical Team) and Louise Daugherty (Genomics England Curation Team) who curated and reviewed the evidence for the genes on the panel.

29.11.2017 Major update to the Intellectual disability gene panel

Today we made a major update to the ID panel, adding extensive reviews of 383 genes by Curators and Clinical fellows at Genomics England who have been investigating the evidence behind these genes in the last few months. The gene rating for these genes was updated according to evidence level, resulting in 66 new Green genes (817 in total) which will be used for genome interpretation. Publications, comments and decisions made based on the evidence can be viewed under the 'Reviews' tab of a gene. The number of total genes on the panel was increased from 1879 to 1895.

17.11.2017 New gene panels

We have added the following panels to PanelApp - if you have expertise in these areas please help us develop these panels by adding genes and reviews:

06.11.2017 We launch a new and improved release of PanelApp!

What's new?

A simpler URL https://panelapp.genomicsengland.co.uk

Direct URL links to panels or genes are available, even if you are not logged in

Straightforward links to genes e.g. https://panelapp.genomicsengland.co.uk/panels/101/CHD7/

Shorter panel codes e.g. https://panelapp.genomicsengland.co.uk/panels/101/

Both Genome build GRCh38 and GRCh37 are supported

This includes updates to some HGNC-approved gene symbols

New webservice queries are available; you can specify assembly GET parameters with either GRch37 (default) or GRch38 as a value. EnsemblIds will be returned for the specified assembly version: GRch37 version 82 or GRch38 version 90 if they exists in the database. For example https://panelapp.genomicsengland.co.uk/WebServices/search_genes/AKT2/?panel_name=Regional%20overgrowth%20disorders&assembly=GRch38

Improved page loading and greatly improved response times

Improvements to the registration process

02.11.2017 A summary of updates to Version 1 panels in October

PanelApp October updates

30.10.2017: PanelApp Update: 167 diagnostic-grade (Version 1+) panels

PanelApp update

20.10.2017 A summary of updates to panels in September

PanelApp September updates

19.09.2017: Diagnostic-grade Pain syndromes gene panel released

A combined panel for Mendelian disorders of pain perception, including insensitivity to pain or increased pain perception has been promoted to Version 1; the green genes on this panel have a high level of evidence and can be used in genome interpretation.

29.08.2017: PanelApp Update: 165 diagnostic-grade (Version 1+) panels

PanelApp update

31.07.2017: PanelApp Update

The Ehlers-Danlos syndromes panel is now Version 1 and ready for patient interpretation!

The number of 'Amber/Watchlist' genes on our Version 1 panels has also taken a jump thanks to a large update of the Intellectual disability panel. Here's a summary of our current Version 1 gene panel statistics:

PanelApp update

27.07.2017: Hirschsprung's disease in the 100,000 Genomes Project.

Our Curator Rebecca Foulger is attending the 3rd Hirschsprung's Disease Conference at Alder Hey Children's hospital, Liverpool, on Friday 28th July to present the ongoing Hirschsprung's gene panel. You can view and review the Familial Hirschsprung Disease panel here. The conference is organised by the charity CHAMPS appeal.

26.07.2017: 19 gene panels launched for reporting pertinent findings in cancer germline genomes

We have released genes panels for pertinent findings in cancer germline genomes, for patients recruited under different tumour types. A big thank you to Clare Turnbull (Clinical Lead for Cancer Genetics and Genomics for 100,000 Genomes Project, Genomics England) for collating these genes lists together, and seeking input from the clinical cancer community.

View and review them here:

20.07.2017: Two skin panels promoted to Version 1

The following two dermatological disorder panels have been promoted to Version 1, which will enable the green (high-level of evidence) genes to be used for genome interpretation. Thank you to Professor John McGrath at King's College London for expert review.

04.07.2017: Latest update of Rare Disease Eligibility Criteria V1.7.2

28.06.2017: PanelApp Presentation

Ellen McDonagh, Head of curation at Genomics England, is currently attending the Curating the Clinical Genome conference in Washington. Ellie is giving a talk on PanelApp and 'The Impact of Community Curation of Gene- Disease Relationships for Clinical Genome Analysis'.

26.06.2017: PanelApp Update:

PanelApp update

15.06.2017: Expert review needed for skin disorder gene panels:

We are currently seeking expert review for the following dermatological disorder panels:

If you have expertise in this area and are able to provide input into these two panels, or have any questions about the panels, please contact panelapp@genomicsengland.co.uk.

06.06.2017: Version 1+ gene panels are ready for patient interpretation!

PanelApp update

31.05.17: Promotion of 6 gene panels to version 1 - now available for genome interpretation

Our curators have been working hard to promote 6 more gene panels to version 1, enabling the green high-level of evidence genes to be used for genome interpretation - thank you to all external reviewers who helped with this achievement:

23.05.17: The latest panel requiring external review is Inherited non-medullary thyroid cancer. Please contact us if you think that you could help with this.

23.05.17: Diagnostic-grade panel for Radial dysplasia

Our latest gene panel to be promoted to Version 1 is Radial dysplasia. This panel contains 58 genes that have been sourced and reviewed, including 47 "green" (diagnostic-grade) genes which can be used for the analysis of patient genomes.

15.05.17: Learn more about PanelApp in this blog by James Hadfield

James Hadfield, Head of Genomics at CRUK Cambridge Institute, has written a short Enseqlopedia blog about PanelApp. Get in touch with us if you have any questions!

Panels requiring external expert review (8th May 2017):

14.05.17: A unified GI tract panel

Ellen, Sarah and our team of reviewers has been working on a combined panel for GI track tumour syndromes, combining three previous panels: Familial colon cancer, Multiple bowel polyps, and Peutz-Jeghers syndrome. The panel is now Version 1, and the diagnostic-grade (green) genes can be used for genome analysis of patients in the 100,000 Genomes Project.

10.05.17: 153 Version 1+ panels!

We now have revised diagnostic-grade green gene lists that can be used for genome analysis for the following diseases:

08.05.17: 151 Version 1+ panels!

Severe hypertriglyceridaemia is our latest gene panel to be promoted to Version 1. That takes our total Version 1+ gene panels to 151!

150 Version 1+ panels!

After our 6th Gene Panel Curation Day last Thursday, we now have 150 Version 1+ panels ready for the analysis of patient genomes, including: Developmental Glaucoma, Familial pulmonary fibrosis and Epidermolysis bullosa Thank you to all our reviewers, curators and clinicians!

02.05.17 PanelApp update

PanelApp update

Our 6th Gene Panel Curation Day

On Thursday 27th April 2017, our Curation and Clinical team will get together at the Wellcome Genome Campus, Hinxton for our 6th Gene Panel Curation day! We'll work together to curate and finalise Version 1 gene panels ready for the analysis of patient genomes. We'll keep you updated on our progress!

25.04.17 PanelApp update

PanelApp update

18.04.17 PanelApp update

PanelApp update

12.04.17 PanelApp webservices (API) are available to query using the examples available on the PanelApp How To tab.

Some gene panels may have been applied for genome analysis and interpretation reports that are now retired and no longer live in webservices or on the PanelApp UI. To access a previously used panel version, use the panel name (rather than the code) and the version number to retrieve the correct panel.

An example is the panel for Bilateral microtia (which is retired on PanelApp because it has now been merged into the Deafness and congenital structural abnormalities panel but can be retrieved by webservices using the specific version number): /crowdsourcing/WebServices/get_panel/Bilateral%20microtia/?version=1.4

10.04.17 PanelApp update

PanelApp update

06.04.17 Rebecca is presenting the poster "PanelApp: A Key Resource for the Rare Disease Community" at the 'Genomics of Rare Disease' conference, Wellcome Genome Campus, Hinxton today (Poster 14) #GRD17

03.04.17 PanelApp update

PanelApp update

29.03.17 "The Impact of Community Curation on Rare Disease Diagnosis" was presented at the 10th International Biocuration Conference, Stanford University by Ellen McDonagh

The presentation included an overview of PanelApp and the curation-crowdsourcing process for creation of rare disease panels.

21.03.17 PanelApp update

PanelApp update

13.03.17 PanelApp update

PanelApp update

06.03.17 PanelApp update

PanelApp update

23.02.17 PanelApp update

PanelApp update

22.02.17 Our 5th Gene Panel Curation Day

Our Curators, Clinical Fellows and Clinical Geneticists got together for the day to discuss genes with difficult scenerios, curate and finalise gene panels: we now have 137 reviewed and revised gene panels! (These are version 1+).

A big thank you to all reviewers who have contributed to these panels, and to everyone involved in the day: Sarah Leigh, Rebecca Foulger, Olivia Niblock, Louise Daugherty, Alice Gardham, Richard Scott, Arianna Tucci, Helen Brittain, Chris Campbell, Ellen Thomas, Damian Smedley, Ellie McDonagh. Thank you also to Antonio Rueda-Martin for essential technical assistance.

The following 7 panels were promoted to version 1 and the green 'diagnostic-grade' genes can now be used for analysis of genomes:

17.02.17 PanelApp Update

PanelApp update

Please see the 41 panels that require expert review:

08.02.17 BRIDGE consortium Tier 1 genes from NIHR BioResource - Rare Diseases Study (NIHRBR-RD) added to PanelApp

We have added the Tier 1 gene list from Inherited bleeding disorders project (BPD). This panel is designed to cover rare inherited bleeding disorders, inherited platelet and thrombotic disorders.

The panel contains green reviews corresponding to BRIDGE consortium Tier 1, as evaluated by the following experts from the BRIDGE consortium NIHRBR-RD contributed to this panel:  

  • Prof Willem Ouwehand, Director NIHR BioResource - Rare Diseases, Cambridge University Hospitals NHS Foundation Trust

  • Dr Keith Gomez, Royal Free Hospital, London

  • Prof Kathleen Freson, Centre for Molecular and Vascular Biology, Leuven, Belgium

  • Prof Michael Laffan, Imperial College, London

  • Dr Andrew Mumford, University of Bristol

  • Dr Ernest Turo, NIHR BioResource - Rare Diseases, Cambridge University Hospitals NHS Foundation Trust

  • Karyn Megy, NIHR BioResource - Rare Diseases, Cambridge University Hospitals NHS Foundation Trust

  • Louise Daugherty, NIHR BioResource - Rare Diseases, Cambridge University Hospitals NHS Foundation Trust

Thank you to Karyn Megy, WGS Clinical Feedback Lead for the NIHR BioResource - Rare Diseases Study (NIHRBR-RD) for providing this list, and to the experts who contributed to the review.

We plan to add further BRIDGE consortium gene lists to PanelApp: watch this space! 

07.02.17 BRIDGE consortium Tier 1 genes from NIHR BioResource - Rare Diseases Study (NIHRBR-RD) added to PanelApp

We have added the Tier 1 gene list from Specialist Pathology: Evaluating Exomes in Diagnostics project (SPEED_NEURO) which covers epilepsies, movement and microcephaly disorders.

The panel contains green reviews corresponding to BRIDGE consortium Tier 1, as evaluated by the following experts from the BRIDGE consortium NIHRBR-RD contributed to this panel:

  • Professor F. Lucy Raymond, Cambridge Institute for Medical Research, University of Cambridge

  • Manju Kurian, Paediatric neurologist, Great Ormond Street Hosptial

  • Keren Carss, NIHR BioResource - Rare Diseases, Cambridge University Hospitals NHS Foundation Trust

  • Alba Sanchis-Juan, NIHR BioResource - Rare Diseases, Cambridge University Hospitals NHS Foundation Trust

  • Marie Erwood NIHR BioResource - Rare Diseases, Cambridge University Hospitals NHS Foundation Trust

  • Louise Daugherty, NIHR BioResource - Rare Diseases, Cambridge University Hospitals NHS Foundation Trust

Thank you to Karyn Megy, WGS Clinical Feedback Lead for the NIHR BioResource - Rare Diseases Study (NIHRBR-RD) for providing this list, and to the experts who contributed to the review.

We plan to add further BRIDGE consortium gene lists to PanelApp: watch this space!

06.02.17 We now have 500 registered reviewers!

PanelApp update

27.01.17 PanelApp Update

PanelApp update

24.01.17 The Ehlers-Danlos syndromes panel was created.

This panel combines genes for Classical Ehlers-Danlos Syndrome, Kyphoscoliotic Ehlers-Danlos syndrome, Ehlers-Danlos Syndrome (unusual phenotypes e.g. absent pain sense) and Ehlers-Danlos syndrome type 3 together. Reviews from these individual panels have been transferred over. Please help us review the genes on this panel to create a diagnostic-grade list of 'green' genes.

23.01.17 Three new disorders have been added to the rare disease list for the 100,000 Genome Project

We have created placeholder gene panels for:

Please click on the panel to add genes and provide your review.

17.01.17 Our first version 2 panel is realised

The Arthrogryposis gene panel was revised to include an additional 101 green genes based on information from diagnostic labs and further curation. As this was such a major change from 10 green genes, the panel was promoted to the next major version 2.0.

10.01.17 PanelApp Update

PanelApp update

44 gene panels still require expert review - if you have expertise in one of these disease areas, please register or sign in to review the genes on the panel to help us establish a diagnostic-grade green list:

03.01.17 Happy New Year to our PanelApp users!

We start the year with 121 version 1 panels covering 147 disorders with a diagnostic green list of genes and a total of 3605 genes. The 65 panels that still require expert review and internal update can be found here: /panels/

We would like to thank all our expert reviewers who contributed to PanelApp in 2016, and welcome those providing reviews this year.

19.12.16 The 4th PanelApp Gene Panel Curation Day

This is when the PanelApp Curators get together in a room with the Clinical Geneticists at Genomics England and revise gene panels according to expert reviews and further curation according to our internal rule set. By getting together in the same room, we can discuss any complicated gene scenerios or evidence issues. Once a panel has been revised, we promote it to version 1; the green genes on this panel will then be used by our Bioinformaticians to help analyse genomes and narrow down potentially diagnostic variants for the 100,000 Genomes Project.

We now have 118 version 1 panels, having promoted 9 gene panels at the Curation Day:

And revised the Malformations of cortical development gene panel to add further genes after an additional expert review.

05.12.16 PanelApp update

PanelApp update

18.11.16 We now have 100 version 1 gene panels! The green genes from these panels are being used to help prioritise variants within patient genomes recruited for the 100,000 Genomes Project.

We also now have 456 reviewers from institutions worldwide - a big thank you to those who have signed up and are reviewing our gene panels!

14.11.16 Our curation team is expanding!

Rebecca Foulger joined Genomics England as a Scientific Curator at the start of October. Rebecca has worked on ontology and database projects since her PhD, including FlyBase, UniProt and the Gene Ontology (GO) project, and she joins us from her Parkinson's disease GO annotation project at UCL.

26.10.16 We now have 95 version 1 gene panels! The green genes from these panels are being used to help prioritise variants within patient genomes recruited for the 100,000 Genomes Project.

The following panels were recently promoted:

06.10.16 We now have 90 version 1 gene panels, of which the green genes are being used to analyse genomes of participants recruited in the 100,000 Genomes Project

Thank you to all the expert reviewers and curators who contributed to these panels. They can be viewed on the panel page by filtering with 'version 1'.

27.09.16 PanelApp was presented both in the UK and in California today

  • PanelApp and the gene panel curation process was presented at the UKGTN Clinical & Scientific Group Meeting in London by Sarah Leigh.

  • PanelApp featured in an overview of the 100,000 Genomes Project presented at Illumina in Santa Clara, California by Ellen McDonagh.

26.09.16 PanelApp was presented in a talk at Stanford University, California, by Ellen McDonagh, in a presentation about the 100,000 Genomes Project.

22.09.16 An overview of the 100,000 Genomes Project was presented by Ellen McDonagh at Genentech, South San Francisco, California, with a focus on the role of the Bioinformatics team and how gene panels on PanelApp are used in the analysis of rare disease genomes for the project.

20.09.16 Ellen McDonagh presented the role of PanelApp as part of a panel discussion about crowdsourcing resources in genomics at the Festival of Genomics, San Diego, California.

16.09.16 PanelApp and an overview of the 100,000 Genomes project was presented by Ellen McDonagh to the Illumina Curation Team, Santa Clara, California.

13.09.16 We now have 87 Version 1 panels!

23.08.16 Updates to Version 1+ panels

4 green genes were added to the Hereditary Ataxia panel Version 1.7:

  • GFAP
  • PRNP
  • GJC2
  • POLR3A 

Changes to the Diabetes with additional phenotypes suggestive of a monogenic aetiology Version 1.1 were made due to feedback from an Expert Reviewer:

  • AGPAT2 added and promoted to green (biallelic)
  • BSCL2 added and promoted to green (biallelic)
  • LRBA added and promoted to green (biallelic)
  • PIK3R1 added and promoted to green (monoallelic)
  • PLIN1 added and promoted to green (monoallelic)
  • POLD1 added and promoted to green (monoallelic)
  • SLC29A3 added and promoted to green (biallelic)
  • TRMT10A added and promoted to green (biallelic)
  • DCAF17 added as red (biallelic)
  • IL2RA added as red (biallelic)
  • PCBD1 added as red (biallelic)
  • STAT1 added as red (monoallelic)
  • IER3IP1 promoted from red to green (biallelic)

22.08.16 Happy Birthday PanelApp!

PanelApp was launched publically a year ago, on 21st August 2015. We now have 151 gene panels (and a placeholder for another 38 disorders), of which 56% have been reviewed and revised to Version 1, providing virtual gene panels for 104 disorders within the 100,000 Genomes Project. There are now being used to help analyse participant genomes. We would like to thank all Reviewers who have contributed their expertise and their time to PanelApp, and helped make this possible.

A big thank you goes to Antonio Rueda-Martin who created PanelApp, developed it and has kept it running successfully. Thank you also to Paul Hayes who has improved usability and created additional features.

Thank you also to all our Curators who have created panels, evaluated reviews and curated further information to revise and improved the panels.

15.08.16 We have 83 Version 1 panels, covering 102 disorders.

These panels have been reviewed and revised internally according to expert review and additional evidence. A big thank you to all reviewers who have contributed to these panels. To view these, go to the full gene panel list and filter for "version 1".

11.08.16 An update about PanelApp will be presented at the UKGTN meeting today, by Ellen McDonagh.

10.08.16 We now have an Activity page, displaying changes made to panels and when reviews are made.

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20.07.16 New features have been added to PanelApp, and improvements to usability have been made!

We show some of these features below...

  • You can now view, search and filter all genes by clicking on the Genes Tab found at the top of the page:

Image1

Image1A

  • You can add a review at the same time as adding a new gene to a panel:

Image2

  • You can now compare two gene panels:

Image3

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Image5

  • There is a new look to the panel page:

Image6

22.06.16 PanelApp is presented at the Curating The Clinical Genome conference 2016 by Ellen McDonagh.

06.06.16 We now have 60 Version 1 gene panels!

These panels have been reviewed and revised internally according to expert review and additional evidence. A big thank you to all reviewers who have contributed to these panels. To view these, go to the full gene panel list and filter for "version 1".

02.06.16 The UKGTN contacted diagnostic lab heads endorsing PanelApp, requesting that labs submitting new NGS gene panel tests confirm the status of genes on PanelApp when relevant diseases are available, and provide reasons for excluding green genes/including red genes. They also encouraged labs to review genes to aid the process.

23.05.16 PanelApp was presented at the Pint of Science Festival to an audience in the Crown Pub in Clerkenwell, London, by Ellen McDonagh.

05.05.16 PanelApp was presented by Dr Katherine Smith at The European School of Genetic Medicine and European Society of Human Genetics Course in Next Generation Sequencing, Bertinoro di Romagna (Italy), May 4-7, 2016.

26.04.16 PanelApp Update

  • We have >300 registered reviewers from around the world.

There are 53 (34%) gene panels with no review...please add your expert review to genes on these panels:

There are 18 (12%) gene panels with a partial review - please add your expert review to these panels to help gain a consensus:

There are 35 revised gene panels (Version 1), covering 46 of the approved rare disorders (22% of the total number of gene panels). Thank you to all reviewers who have contributed to these panels:

18.04.16 Additional webservices are available, allowing you to search PanelApp by gene:

  • Search for panels by gene: /crowdsourcing/WebServices/search_genes/BTK/

  • Search for a gene in one panel: /crowdsourcing/WebServices/search_genes/BTK/?panel_name=Intellectual%20disability&format=json

  • Search by a gene, and pull out information only when it is rated green: /crowdsourcing/WebServices/search_genes/BTK/?&LevelOfConfidence=HighEvidence&format=json

  • Search by gene from a particular source (e.g. UKGTN): /crowdsourcing/WebServices/search_genes/BTK/?&Evidences=UKGTN&format=json

  • For all genes in a panel: /crowdsourcing/WebServices/search_genes/all/?panel_name=Intellectual%20disability&format=json

15.04.16 PanelApp is now one of the databases included on the BioSharing site.

Biosharing is a curated, searchable portal of inter-related data standards, databases, and policies in the life, environmental and biomedical sciences.

12.04.16 A talk on PanelApp was given at the 9th International Biocuration Conference in Geneva by Ellen McDonagh.

The methods behind curating the gene panels and gaining expert knowledge through crowdsourcing were presented.

08.04.16 PanelApp website is now available within the N3 network, and so issues accessing it within the NHS should now be resolved.

We apologise for any inconvenience this may have caused, and appreciate the feedback we have had from users.

05.04.16 The BRCA1 gene within the intellectual disability panel was demoted from green to red.

30.03.16 Update on changes to gene panels

A combined Beckwith-Wiedemann syndrome (BWS) and other congenital overgrowth disorders gene panel was created, combining the individual gene panels for the following disorders together:

  • Classical Beckwith-Wiedemann syndrome
  • Atypical Beckwith-Wiedemann syndrome
  • Simpson-Golabi-Behmel syndrome
  • Sotos syndrome
  • Weaver syndrome

Expert review of these panels was used to create Version 1 of the Beckwith-Wiedemann syndrome (BWS) gene panel.

24.03.16 Update on changes to gene panels

Reviews from experts for the following gene panels have been internally evaluated. Using the reviews and other sources, the gene panels have been revised by Genomics England Curators and upgraded to Version 1.0. The green genes of these revised gene panels will be used for analysis of genomes for patients recruited under these disorders. We would like to thank all reviewers who have contributed to this effort - names and affiliations of those who have contributed are provided on each gene panel page.

Other changes to panels:

Gene panels for Cone Dysfunction Syndrome, Developmental macular and foveal dystrophy, Inherited macular dystrophy, Inherited optic neuropathies, Leber Congenital Amaurosis / Early-Onset Severe Retinal Dystrophy, Rod Dysfunction Syndrome and Rod-cone dystrophy were combined into a Posterior segment abnormalities virtual gene panel.

14.03.16 Please be aware that PanelApp was experiencing technical issues and may have been unavailable to users.

We apologise for any inconvenience this may haved caused - the issue is now fixed. Please contact panelapp@genomicsengland.co.uk if you experience any difficulties accessing panels, or cannot see reviews you have made.

29.02.16 Rare Disease Day

Contribute to rare disease genome analysis by reviewing panels on PanelApp if you have an expertise in a particular disease or gene.

23.02.16 PanelApp was included in a presentation by Dr Emma Baple at the NHS Genomics Medicine Centre (GMC) National Event.

For the 100,000 Genomes Project Rare Disease Program, Emma explained how variants from genome analysis are tiered using the green genes from a relevant gene panel in PanelApp, highlighting the importance of expert review of the panels for feeding back results to GMCs.

19.02.16 Gene panel news

Today there were announcements in the press regarding the publication of a comprehensive sequencing assay for inherited cardiac conditions (ICC).

The genes in their table of well-characterised, disease-causing genes (Table 1) are all currently rated green (diagnostic grade) within the relevant panels on PanelApp:

The full published ICC panel contains disease-causing, putatively pathogenic, research and phenocopy genes (supplemental Table S1). Genes on the full ICC panel were compared against genes within the relevant panels on PanelApp. Several additional genes were added to the following panels: Arrhythmogenic Right Ventricular Cardiomyopathy, Brugada syndrome, Catecholaminergic Polymorphic Ventricular Tachycardia, Dilated Cardiomyopathy, Dilated Cardiomyopathy and conduction defects, Familial Thoracic Aortic Aneurysm Disease, Familial hypercholesterolaemia, Hypertrophic Cardiomyopathy, Long QT syndrome.

We are asking experts to review the genes on the panels to determine whether there is enough evidence for these genes to be diagnostic-grade (and should be rated green), or whether it is a research gene ( and should be rated red).

18.02.16: We now have 300 registered reviewers!

11.02.16 Update on changes to gene panels

Reviews from experts for the following gene panels have been internally evaluated. Using the reviews and other sources, the gene panels have been revised by Genomics England Curators and upgraded to Version 1.0. The green genes of these revised gene panels will be used for analysis of genomes for patients recruited under these disorders. We would like to thank all reviewers who have contributed to this effort - names and affiliations of those who have contributed are provided on each gene panel page.

Other changes to panels:

10.02.16 Vimeo videos are now available that provide an introduction to PanelApp, and instructions for reviewing gene panels on PanelApp.

These were updated from our original videos, due to the new design of the user interface in December 2015 by Paul Hayes and Antonio Rueda. Thank you very much to Luke Webster (QMUL) and Lisa Dinh (Genomics England) for helping to create and publish these videos. The voice is Ellen McDonagh, Lead Scientific Curator at Genomics England.

The same videos are also available on YouTube:

29.01.16:

  • The eligibility statement for Familial Thoracic Aortic Aneurysm Disease was updated, and the TGFBR2 gene was added to the eligibility statement prior genetic testing genes.

  • A gene within the prior genetic testing for the Multiple bowel polyps panel was corrected from "MHS6" to "MSH6".

19.01.16: PanelApp webservices are now available to query using the following examples...

  • Get a list of the panel names:

/crowdsourcing/WebServices/list_panels

  • Get individual panels (last version of the panel by default):

/crowdsourcing/WebServices/get_panel/Epileptic%20encephalopathy/

  • Select a specific version of a panel (version=X.X):

/crowdsourcing/WebServices/get_panel/Epileptic%20encephalopathy/?version=0.1

  • Filter the genes by level of confidence:

example 1 (green genes): /crowdsourcing/WebServices/get_panel/Epileptic%20encephalopathy/?LevelOfConfidence=HighEvidence

example 2 (green genes, red genes): /crowdsourcing/WebServices/get_panel/Epileptic%20encephalopathy/?LevelOfConfidence=HighEvidence,LowEvidence

  • Filter the genes by mode of inheritance (example):

/crowdsourcing/WebServices/get_panel/Epileptic%20encephalopathy/?LevelOfConfidence=HighEvidence,LowEvidence&modesOfInheritance=biallelic

Terms available to use:

  • "MONOALLELIC, autosomal or pseudoautosomal, NOT imprinted": "monoallelic_not_imprinted"

  • "MONOALLELIC, autosomal or pseudoautosomal, maternally imprinted (paternal allele expressed)": "monoallelic_maternally_imprinted"

  • "MONOALLELIC, autosomal or pseudoautosomal, paternally imprinted (maternal allele expressed)": "monoallelic_paternally_imprinted"

  • "MONOALLELIC, autosomal or pseudoautosomal, imprinted status unknown": "monoallelic"

  • "BIALLELIC, autosomal or pseudoautosomal": "biallelic"

  • "BOTH monoallelic and biallelic, autosomal or pseudoautosomal": "monoallelic_and_biallelic"

  • "BOTH monoallelic and biallelic (but BIALLELIC mutations cause a more SEVERE disease form), autosomal or pseudoautosomal": "monoallelic_and_more_severe_biallelic"

  • "X-LINKED: hemizygous mutation in males, biallelic mutations in females": "xlinked_biallelic"

  • "X-LINKED: hemizygous mutation in males, monoallelic mutations in females may cause disease (may be less severe, later onset than males)": "xlinked_monoallelic"

  • "MITOCHONDRIAL": "mitochondrial"

  • "Unknown": "unknown"

11.01.16: Initial gene panels for new nominated rare diseases.

Gene panels for the following diseases have been created on PanelApp, allowing genes to be added by expert review. If you think other existing gene panels should be applied to one of these panels, please contact panelapp@genomicsengland.co.uk.

08.01.16: Changes to some eligibility statements, and new gene panels added.

Initial gene panels for the following diseases have been created on PanelApp, allowing genes to be added by expert review. If you think other existing gene panels should be applied to one of these panels, please contact panelapp@genomicsengland.co.uk.

Ciliopathies

Dermatological disorders

Dysmorphic and congenital abnormality syndromes

Neurology and neurodevelopmental disorders

18.12.15: PanelApp is presented to Dame Una O’Brien, Permanent Secretary at the Department of Health.

15.12.15: A new look for PanelApp is launched to make viewing and reviewing gene panels easier.

10.12.15: A gene panel for undiagnosed neurocutaneous disorders has been added to PanelApp.

07.12.15: We now have 250 reviewers registered!

19.11.15: Gene panels for the following new rare disorders have been added to PanelApp:

13.11.15: The Intellectual disability and Epileptic encephalopathy gene panels were updated to reflect expert reviewer ratings.

03.11.15: Gene panels for the following new rare disorders have been added to PanelApp:

02.11.15: Gene panels are now available to review for the following new rare disorders:

26.10.15: Read a blog by the PHG Foundation PanelApp – the catalyst to drive improved gene panel testing?

24.10.15: OpenHelix Video Tip of the Week: PanelApp, from the 100,000 Genomes Project

23.10.15: Presentation at the Italian Society of Human Genetics National Congress, Rimini (Ellen McDonagh).

23.10.15: Presentation at the Cardiovascular GeCIP Domain Meeting, London (Augusto Rendon)

22.10.15: We now have 200 experts registered!

21.10.15: Presentation at the GMC/GeCIP Event, London (Ellen McDonagh).

16.10.15: Listen to this week's RARECast (Global Genes) podcast featuring an interview about PanelApp.

15.10.15: PanelApp software version has been updated, making downloads much faster!

01.10.15: PanelApp update

  • Formatted excel spreadsheets of large gene panels (>50 genes) are available for download from the 'Large gene panels' section above, allowing reviewers to add their gene evaluations to the excel spreadsheet in a standardised way and submit their review for upload to PanelApp.

  • An update to the disclaimer was made.

30.09.15: We now have over 100 reviewers registered!

24.09.15: Thank you to all reviews that have been made so far!

View the list of 120 gene panels that still require expert review to find the rare disease in your area of expertise

23.09.15: PanelApp videos are now available on Vimeo; introductory video to PanelApp, and a video to help Expert Reviewers.

11.09.15: PanelApp videos released

An introductory video to PanelApp, and another to help Expert Reviewers are released on YouTube.

09.09.15: Read an article by the PHG Foundation regarding PanelApp

08.09.15: The PanelApp Handbook PDF is now available from the homepage.

02.09.15: PanelApp Update

  • 15 new gene panels are released for each of the new Fast-Track disorders.
  • PanelApp is presented at the NHS Expo 2015 in Manchester.

25.08.15: PanelApp presentation at the NHS GMC National Event.

21.08.15: PanelApp is piloted. Version 0 of the gene panels are released for public view and for expert review.

09.04.15: The first line of code for PanelApp is created.

PanelApp Reviewers

PanelApp has a crowdsourcing review tool to allow each gene to be reviewed and commented on by experts within the scientific community. Reviewers of PanelApp are worldwide; we currently have more than 500 experts registered from 25 different countries. To become a reviewer, register here

We are asking expert reviewers of the gene panels to help establish a consensus “Green” diagnostic grade list of genes that have a high level of evidence for a role in the relevant rare disease.

Why be a reviewer?

Desired reviewer experience

  • Reviewers can have an academic, clinical and/or commercial background.

  • Can be based anywhere in the world. We currently have registered reviewers from Argentina, Australia, Austria, Bangladesh, Brazil, Canada, France, Germany, Hong Kong, India, Italy, Japan, Korea, Kuwait, Netherlands, New Zealand, Portugal, Qatar, South Korea, Spain, Switzerland, Thailand, Turkey, USA and the UK.

In order to encourage expert review of the gene panels, we would request that reviewers of the gene panels should have at least one of the following:

  • Expertise in a disease area relevant to the diseases that are part of the 100,000 Genomes Project.
  • Expertise in diagnostic genetic testing of a disease area relevant to the diseases that are part of the 100,000 Genomes Project.
  • Expertise in genes that are relevant to the diseases that are part of the 100,000 Genomes Project.

A full list of the rare diseases that are part of the 100,000 Genomes Project can be found on the Genomics England website. A list of relevant tumour types can also be found via the Genomics England website.

What can Reviewers do on PanelApp?

Reviewers can:

  • View gene panels.
  • View gene information.
  • Download gene panels.
  • Rate genes in a gene panel.
  • Provide gene evaluations and comments.
  • View other reviewers’ ratings, evaluations and comments and who made these.
  • View a list of their own evaluations.
  • Add genes to panels (will be indicated in grey until a Genomics England Curator evaluates the evidence for the gene).
  • Link to other sources related to the gene such as OMIM (disease-related information), ClinVar (variant-disease related information).
  • View gene history.

Reviewers cannot:

  • Delete genes from a panel.
  • Delete panels

What are we asking of reviewers?

  • Read the description of the disease in the description box on the panel in order to have an idea of the phenotype criteria established for patient inclusion. This is usually the eligibility criteria for recruitment to the 100,000 Genomes Project.

  • Click on each gene in the panel to provide a review using the review gene tool (pictured).

PanelApp sign in

  • Assess whether each gene in the list should either be on the Green list (high evidence, clinically-actionable variants, diagnostically reportable) or Red list (low evidence or variants that are not clinically actionable) for the rare disease category: please read the criteria for the evidence level required on the Guidelines tab.

  • Provide justifications in the comments box and/or publications when promoting/demoting a gene in order to support the decision to change its status on the panel.

  • Provide a mode of inheritance for the gene (gene-disease association).

  • If loss-of-function variants (as defined by the sequence ontology terms detailed below) do not cause the disease phenotype, please select an option in the mode of pathogenicity pulldown menu and provide further details as a comment. If a curated set of known-pathogenic variants is available for this gene-phenotype, please contact us at panelapp@genomicsengland.co.uk.

  • If submitting the gene evaluation on behalf of a clinical laboratory, indicate whether variants in the gene are reported as part of current diagnostic practice by checking the 'Clinical diagnostic' box.

  • Add publications, phenotypes and any important comments (such as the transcript used to report against in the reviewer’s clinical practice, the age of disease onset or penetrance).

  • Add any missing genes using the tool found at the bottom of the gene panel page (pictured). Provide a rating for the new gene. New genes should be promoted to the green list only if there is significant confidence in reporting in a diagnostic setting (Guidelines for the evidence required for gene ratings are available via the Guidelines tab). Genes that are still in research phase that require further evidence can be added to a panel – select ‘research’ as a source. These should be rated as low evidence (red list).

PanelApp sign in

Instructions for registering to be a reviewer

  • Go to PanelApp registration page and select Register to be a reviewer.

  • Fill in the information and submit your request by clicking the “Register” button.

Username and password: These are needed to set up and sign in to your reviewer account.

First Name, Last Name and Affiliation: To encourage openness, all gene evaluations and comments from reviewers will be public. Your full name and affiliation will be added to your reviews when you are signed in to your reviewer account. By signing up to be a reviewer, you are agreeing to this condition.

Role, Workplace and Group: We are collecting this information in order to get a sense of a reviewer’s background, this information will not be displayed.

Email: please use your institute email (e.g. @qmul.ac.uk) to register if possible. This will allow us to process the reviewer request more effectively. If your application is accepted, you will receive confirmation of your reviewer status to this email address.

  • After registering, you will be automatically signed in with your new username, but will still only have public access and will not be able to make gene evaluations or comments. We will review your application and if accepted, you will be sent an email with confirmation and further instructions. You will need to click the link in this email to activate your account.

Please contact panelapp@genomicsengland.co.uk for any enquires or if you have issues signing in.

How to make a review

Log in

Log in as a reviewer - enter your username and password and click “Log in”.

Read information about PanelApp

You will be directed to the PanelApp homepage, where you can find out more about PanelApp, how gene panels were initially constructed, the role of expert reviewers and gene panel guidelines.

Find gene panels

To find the gene panel(s) assigned to you or relevant to your disease area, click on “Panels” in the top bar of the page. You can see all gene panels listed. The list can be sorted by panel name, number of evaluated genes or number of reviewers. The "Filter panels" box allows users to find gene panels of interest e.g. by entering "diabetes", the list will be filtered to display all panels related to diabetes.

Read the eligibility statement for the rare disease

We request that reviewers read the details regarding the panel in the description box. For the rare diseases this will be the eligibility statement for the 100,000 Genomes Project (where available). The description provides information on the phenotype inclusion and exclusion criteria for the panel.

Rate the genes in the gene panel

Click on each gene in the panel and provide a review using the ‘Reviews’ tab. Please leave feedback for each gene on a panel, specifically:

  • Provide a rating (Green/high evidence/clinically-actionable or diagnostically reportable variants OR Red/low evidence/variants that are not clinically actionable). You may also choose Amber evidence (I don’t know) if it is a borderline case or you are unsure (Guidelines for the evidence required for gene ratings are available via the Guidelines) tab
  • Provide justifications in the comments box and/or publications when promoting/demoting a gene in order to support the decision to change its status on the panel.
  • When you have reviewed a gene, you can see your review under the review tab along with others. A tick will appear against the gene on the left hand side gene list, and on the main panel page genes you have reviewed are also denoted.

Considerations when reviewing:

  • Should this gene be on the Green list (high evidence, there is strong evidence for variants in this gene to be disease causing), or on the Red list (low evidence, there is little support for variants in this gene to be reported as disease-causing)? (See the Gene Panel Guidelines & Principles tab).
  • Would you be confident reporting a pathogenic or likely pathogenic variant within all the genes within the green list, in relation to the specified disorder?
  • Are any genes missing from the list? (See the How to... tab).
  • Are any of these genes known to be associated with the phenotype but not clinically actionable? For example, they are too big/too variable/there are uncertain effects of variation? In which case, they should be on the red list.
  • Information for genes on the red list will still be maintained for future reference and may be utilised to prioritise tier 3 variants. As more evidence emerges, may be promoted to the green list.
  • As an aid in the reviewing process, links to OMIM and ClinVar databases are provided (under Details).

Provide mode of inheritance

For each gene, select a mode of inheritance from the drop down menu and submit. Definitions for the terms are provided via the "?" button, and in the Glossary section of the Contact, Sources and Glossary tab.

If the mode of inheritance you want to add is not within the drop down menu, or you know of more than one mode of inheritance pattern, different modes of inheritance for specific phenotypes, or other scenarios, please select “other” and provide details in the comments box. Please provide information regarding imprinting, if known.

Provide additional information

Mode of pathogenicity: We would like to collect exceptions to the rule that loss-of-function variants in this gene can cause the disease. Loss-of-function variants are defined as variants with the sequence ontology terms; transcript ablation, splice acceptor variant, splice donor variant, stop gained, frameshift variant, stop lost, initiator codon variant/start lost.

If loss-of-function variants do not cause the phenotype select “Loss-of-function variants (as defined in pop up message) DO NOT cause this phenotype", and provide details in the comments.

Considerations when reviewing:

  • An example of an exception to the rule is the PCSK9 gene, where loss-of-function variants are not relevant for hypercholesterolemia, whereas gain-of-function variant are associated with this phenotype PMID: 12730697.
  • There may be known pathogenic variants in a gene in addition to loss-of-function variants – if a curated set of known-pathogenic variants is available for a gene-phenotype association, please contact us at: panelapp@genomicsengland.co.uk

Phenotypes: Please add phenotypes using standardised OMIM or HPO terms/codes if any additional phenotypes are known to be associated with this gene relevant to the rare disease category (level 4 title). The phenotypes shown in PanelApp are those collected from the sources, with relevance to the disease category (level 4 title).

Publications: Please provide PubMed IDs in the format PMID: 12345678;23456789;34567891. Include publications that provide supporting evidence for your given rating e.g. published family pedigree studies, variant reports, functional studies etc supporting the gene-phenotype association. Publications demonstrating a lack of association between the gene and phenotype should also be included.

Comments: Any additional important information, notes of clarification or comments to stimulate debate can be provided in the comments box.

Considerations when reviewing:

  • Your evaluation and comments will be tagged with your reviewer name and is public.
  • The date you made your review will appear, along with the version of the panel you reviewed.
  • You can make multiple comments and edit or delete them individually.
  • Your review inputs in the review gene tool are saved and so will appear when you log in again.
  • Changes to rating, mode of inheritance, mode of pathogenicity and current diagnostic using the gene evaluation tool will overwrite your initial evaluation.
  • Publications and phenotypes will be saved in the evaluation tool and can be added to; please note that if you delete what has been saved in these boxes, your original submissions of publications and phenotypes will be overwritten.

How to view your evaluations

Click on the “Logged in as: …” button in the top right hand corner of the screen to view your user information and a list of your evaluations. Click on the “Go to Gene Evaluations” to make changes or edits to your evaluation, or click on the panel name to view the entire gene panel.

Large gene panels and groups of disorders

For more detailed guidance about reviewing PanelApp please download our revised handbook version 5.7

For large gene panels or panels for groups of disorders we understand that reviewing using PanelApp may be difficult. We can provide formatted excel sheets of the panels, allowing reviewers to add their reviews to the file for upload to PanelApp. As our panels change over time, please contact us to request the latest version by emailing panelapp@genomicsengland.co.uk.

This is interim information and has not yet received final approval from Genomics England internal governance processes or NHS England and is therefore potentially subject to change.

Gene Panel Guidelines

How to rate the genes

Genes included in a Genomics England gene panel for a rare disease category (Green list) should fit the criteria A-E outlined below.

These guidelines were developed as a combination of the ClinGen DEFINITIVE evidence for a causal role of the gene in the disease(a), and the Developmental Disorder Genotype-Phenotype (DDG2P) CONFIRMED DD Gene evidence level(b) (please see the original references provided below for full details). These help provide a guideline for expert reviewers when assessing whether a gene should be on the green or the red list of a panel.

A. There are plausible disease-causing mutations(i) within, affecting or encompassing an interpretable functional region(ii) of this gene identified in multiple (3 or more) unrelated cases/families with the phenotype(iii).

OR

B. There are plausible disease-causing mutations(i) within, affecting or encompassing cis-regulatory elements convincingly affecting the expression of a single gene identified in multiple (>3) unrelated cases/families with the phenotype(iii).

OR

C. As definitions A or B but in 2 or 3 unrelated cases/families with the phenotype, with the addition of convincing bioinformatic or functional evidence of causation e.g. known inborn error of metabolism with mutation in orthologous gene which is known to have the relevant deficient enzymatic activity in other species; existence of an animal model which recapitulates the human phenotype.

AND

D. Evidence indicates that disease-causing mutations follow a Mendelian pattern of causation appropriate for reporting in a diagnostic setting(iv).

AND

E. No convincing evidence exists or has emerged that contradicts the role of the gene in the specified phenotype.

(i)Plausible disease-causing mutations: Recurrent de novo mutations convincingly affecting gene function. Rare, fully-penetrant mutations - relevant genotype never, or very rarely, seen in controls. (ii) Interpretable functional region: ORF in protein coding genes miRNA stem or loop. (iii) Phenotype: the rare disease category, as described in the eligibility statement. (iv) Intermediate penetrance genes should not be included.

References:

(a) ClinGen Clinical Validity Classifications originally dated July 2014, and updated Oct 2015 A preprint publication is now available: Evaluating the clinical validity of gene-disease associations: an evidence-based framework developed by the Clinical Genome Resource. Strande et al

(b) The Development Disorder Genotype - Phenotype Database and PMID: 25529582.

Guidelines were updated 10th November 2017; change made was convertion of >3 to 3 or more after internal clinical approval, to reflect curation practices.

Gene Panel Principles

  • For each rare disorder category, the panel should be a conservative “diagnostic grade” set of genes that out of the whole genome should be examined first, as variants within these genes are most likely to cause/explain the disease phenotype.
  • A conservative list of genes of known clinical utility and scientific validity is required.
  • We acknowledge that the panel therefore will be missing genes that have been reported in association with the disease/phenotype but where the level of proof has not reached that required for it to enter use in a diagnostic setting. Variants that have passed the standard filtering criteria but are not within the gene panel for the relevant disease category will be assigned to a separate tier (Tier 3).
  • Genes included on the panel may have been screened in the patient previously; however, with whole genome sequencing, we may find variants of interest not well covered by exome screens or missed by other methods.
  • A single gene may appear in multiple gene panels.
  • Genes may also be associated with other phenotypes not indicated in the gene panel.
  • The gene panels will be updated as we learn from newly published evidence and the 100,000 Genomes Project participant data.

This is interim information and has not yet received final approval from Genomics England internal governance processes or NHS England and is therefore potentially subject to change.

PanelApp WebServices

Retired panels

Some gene panels may have been applied for genome analysis and interpretation reports that are now retired and are no longer live in webservices or on the PanelApp UI. To access a previously used panel version, use the panel name or the code and the version number to retrive the correct panel.

An example is the panel for Bilateral microtia (which is retired on PanelApp because it has now been merged into the Deafness and congenital structural abnormalities panel but can be retrieved by webservices using the specific version number):

https://panelapp.genomicsengland.co.uk/WebServices/get_panel/Bilateral microtia/?version=1.4

https://panelapp.genomicsengland.co.uk/WebServices/get_panel/553fa00ebb5a161c1b6faa6e/?version=1.4

A full list of retired version 1 panels and their codes:

List Panels

Endpoint: https://panelapp.genomicsengland.co.uk/WebServices/list_panels/

Returns the list of panels

{ "result": [ { "DiseaseGroup": "Ophthalmological disorders", "Number_of_Genes": 54, "Name": "Anophthalmia/microphthamia", "Panel_Id": "553f97abbb5a1616e5ed45f9", "CurrentVersion": "1.8", "DiseaseSubGroup": "Ocular malformations", "Relevant_disorders": [ "Anophthalmia or microphthamia" ] } ] }

Filtering

Parameters:

  • Name : Filters the list by panel name

Examples

  • https://panelapp.genomicsengland.co.uk/WebServices/list_panels/
  • https://panelapp.genomicsengland.co.uk/WebServices/list_panels/?Name=Ocular%20malformations

Get Panel Info

Endpoint https://panelapp.genomicsengland.co.uk/WebServices/get_panel/{Panel ID | Panel Name}/ Returns Panel info

{ "result": { "Genes": [ { "Publications": null, "ModeOfPathogenicity": null, "Evidences": [ "Emory Genetics Laboratory", "Expert Review Green" ], "EnsembleGeneIds": [ "ENSG00000054598" ], "GeneSymbol": "FOXC1", "ModeOfInheritance": "monoallelic", "Phenotypes": null, "Penetrance": "Complete", "LevelOfConfidence": "HighEvidence" } ], "DiseaseSubGroup": "Ocular malformations", "version": "1.8", "SpecificDiseaseName": "Anophthalmia/microphthamia", "DiseaseGroup": "Ophthalmological disorders" } }

Filtering

Parameters:

  • ModeOfInheritance : comma separated list of modes of inheritance, one of the following values:

    • monoallelic_not_imprinted
    • monoallelic_maternally_imprinted
    • monoallelic_paternally_imprinted
    • monoallelic
    • biallelic
    • monoallelic_and_biallelic
    • monoallelic_and_more_severe_biallelic
    • xlinked_biallelic
    • xlinked_monoallelic
    • mitochondrial
    • unknown
  • ModeOfPathogenicity : comma separated list of modes of pathogenicities, one of the following values:

    • loss_of_function
    • other
  • Penetrance : comma separated list of penetrance values, one of the following:

    • unknown
    • Complete
    • Incomplete
  • LevelOfConfidence : comma separated list of confidence levels, one of the following:
    • HighEvidence
    • ModerateEvidence
    • LowEvidence
  • version : Panel version

Examples

  • https://panelapp.genomicsengland.co.uk/WebServices/get_panel/553f97abbb5a1616e5ed45f9/
  • https://panelapp.genomicsengland.co.uk/WebServices/get_panel/Anophthalmia/
  • https://panelapp.genomicsengland.co.uk/WebServices/get_panel/Anophthalmia/?ModeOfInheritance=biallelic,monoallelic
  • https://panelapp.genomicsengland.co.uk/WebServices/get_panel/Anophthalmia/?ModeOfPathogenicity=loss_of_function
  • https://panelapp.genomicsengland.co.uk/WebServices/get_panel/Anophthalmia/?Penetrance=Complete
  • https://panelapp.genomicsengland.co.uk/WebServices/get_panel/Anophthalmia/?LevelOfConfidence=HighEvidence,ModerateEvidence
  • https://panelapp.genomicsengland.co.uk/WebServices/get_panel/Anophthalmia/?version=1.7
  • https://panelapp.genomicsengland.co.uk/WebServices/get_panel/553f97abbb5a1616e5ed45f9/?version=1.7

Search by Gene

Endpoint https://panelapp.genomicsengland.co.uk/WebServices/search_genes/{Comma separated list of gene symbol}/

{ "results": [ { "SpecificDiseaseName": "Insulin resistance (including lipodystrophy", "Publications": [ "15166380", "17327441", "17576055" ], "Phenotypes": [ "Diabetes mellitus, type II\t125853" ], "EnsembleGeneIds": [ "ENSG00000105221" ], "Evidences": [ "Expert Review Red", "Radboud University Medical Center, Nijmegen", "Emory Genetics Laboratory", "Literature" ], "DiseaseGroup": "Endocrine disorders", "ModeOfInheritance": "monoallelic_not_imprinted", "DiseaseSubGroup": "Disorders of unusual phenotypes", "LevelOfConfidence": "LowEvidence", "ModeOfPathogenicity": null, "GeneSymbol": "AKT2", "version": "1.2", "Penetrance": "Complete" }, { "SpecificDiseaseName": "Multi-organ autoimmune diabetes", "Publications": null, "Phenotypes": [ "Diabetes mellitus, type II, 125853", " Hypoinsulinemic hypoglycemia with hemihypertrophy, 240900" ], "EnsembleGeneIds": [ "ENSG00000105221" ], "Evidences": [ "Expert Review Removed", "Radboud University Medical Center, Nijmegen" ], "DiseaseGroup": "Endocrine disorders", "ModeOfInheritance": null, "DiseaseSubGroup": "Disorders of unusual phenotypes", "LevelOfConfidence": "NoList", "ModeOfPathogenicity": null, "GeneSymbol": "AKT2", "version": "1.4", "Penetrance": "Complete" }, { "SpecificDiseaseName": "Regional overgrowth disorders", "Publications": null, "Phenotypes": [ "Hypoinsulinemic hypoglycemia with hemihypertrophy,240900", "Hypoinsulinemic hypoglycemia with hemihypertrophy", " HIHGHH", "Hypoinsulinemic hypoglycemia with hemihypertrophy, 240900" ], "EnsembleGeneIds": [ "ENSG00000105221" ], "Evidences": [ "Other", "Radboud University Medical Center, Nijmegen" ], "DiseaseGroup": "", "ModeOfInheritance": "monoallelic", "DiseaseSubGroup": "", "LevelOfConfidence": "LowEvidence", "ModeOfPathogenicity": null, "GeneSymbol": "AKT2", "version": "1.3", "Penetrance": "Complete" } ], "meta": { "numOfResults": 3 } }

Filtering

Parameters: - ModeOfInheritance: comma separated list of modes of inheritance, one of the following values:

-  monoallelic_not_imprinted 
-  monoallelic_maternally_imprinted 
-  monoallelic_paternally_imprinted 
-  monoallelic 
-  biallelic 
-  monoallelic_and_biallelic 
-  monoallelic_and_more_severe_biallelic 
-  xlinked_biallelic 
-  xlinked_monoallelic 
-  mitochondrial 
-  unknown
  • ModeOfPathogenicity : comma separated list of modes of pathogenicities, one of the following values:

    • loss_of_function
    • other
  • Penetrance : comma separated list of penetrance values, one of the following:

    • unknown
    • Complete
    • Incomplete
  • LevelOfConfidence : comma separated list of confidence levels, one of the following:

    • HighEvidence
    • ModerateEvidence
    • LowEvidence
  • Evidences : comma separated list of evidences, one of the following:

    • radboud_university_medical_center_nijmegen
    • illumina_trugenome_clinical_sequencing_services
    • emory_genetics_laboratory
    • ukgtn
    • other
    • export_list
    • export_review
    • literature
    • eligibility_statement_prior_genetic_testing
    • research
  • panel_name : only search specified panel names, comma separated list

Examples

  • https://panelapp.genomicsengland.co.uk/WebServices/search_genes/AKT2/
  • https://panelapp.genomicsengland.co.uk/WebServices/search_genes/AKT2/?ModeOfInheritance=biallelic,monoallelic
  • https://panelapp.genomicsengland.co.uk/WebServices/search_genes/AKT2/?ModeOfPathogenicity=loss_of_function
  • https://panelapp.genomicsengland.co.uk/WebServices/search_genes/AKT2/?Penetrance=Complete
  • https://panelapp.genomicsengland.co.uk/WebServices/search_genes/AKT2/?LevelOfConfidence=HighEvidence,ModerateEvidence
  • https://panelapp.genomicsengland.co.uk/WebServices/search_genes/AKT2/?Evidences=literature
  • https://panelapp.genomicsengland.co.uk/WebServices/search_genes/AKT2/?panel_name=Regional%20overgrowth%20disorders

Additional parameters

Additionally, you can specify assembly GET parameters with either GRch37 (default) or GRch38 as a value. EnsemblIds will be returned for the specified assembly version: GRch37 version 82 or GRch38 version 90 if they exists in the database. - https://panelapp.genomicsengland.co.uk/WebServices/search_genes/AKT2/?panel_name=Regional%20overgrowth%20disorders&assembly=GRch38

Frequently Asked Questions

Why gene panels?

The finalised ‘Green’ genes on a Version 1+ gene panel will be used in the tiering of variants in order to aid clinical interpretation of the genomes sequenced as part of the 100,000 Genomes Project. As the virtual gene panels are publically accessible, they are also available for the scientific and clinical communities.

Why are you asking experts to review the gene panels?

The aim is to utilise expertise and knowledge from the Scientific Community to establish consensus gene panels (a defined green list) for each rare disease category.

Can experts not in the UK or not directly involved in the 100,000 Genomes Project be a reviewer?

Yes! We would like to encourage those with expertise in rare diseases from around the world to register and review genes and gene panels on PanelApp to help gain a consensus view of which genes have enough evidence to be included on a diagnostic virtual gene panel. We currently have more than 500 experts registered from 25 different countries (Argentina, Australia, Austria, Bangladesh, Brazil, Canada, France, Germany, Hong Kong, India, Italy, Japan, Korea, Kuwait, Netherlands, New Zealand, Portugal, Qatar, South Korea, Spain, Switzerland, Thailand, Turkey, USA, UK).

As an expert reviewer, how do I rate the genes?

Genes included in a Genomics England gene panel for a rare disease category (green list) should fit the criteria A-E outlined on the Guidelines tab.

Review Scenerios

For the congenital non-syndromic hearing loss (profound/severe) panel

a. A gene is proven to cause syndromic hearing loss but has not to date been proven to manifest with non-syndromic hearing loss. Should it be included in the panel?

Yes, we feel that these genes should be included as a Tier 1 variant in this gene is likely to be relevant to this individual (for example highlighting additional medical features that should be looked for) and should therefore be reported in the genome interpretation.

b. A gene is proven to cause hearing loss, but not congenital profound/severe hearing loss. Should it be included in the panel?

Yes, we feel that these genes should be included as a Tier 1 variant in this gene is likely to be relevant to this individual (even if only partially explaining the phenotype) and should therefore be reported in the genome interpretation.

What will the gene panels and information I provide be used for?

The gene lists and connected information, such as mode of inheritance and pathogenicity, will be used to aid tiering of variants identified in a patient with that disease category, thus will aid genome interpretation and the reporting of clinically-relevant information and may contribute to the diagnosis of the patient. In addition, the gene panels are publically available and open for research use for the benefit the scientific community.

Who will be able to access the gene panels?

Anyone can view and download the gene panels. In addition, registered reviewers can evaluate genes on the gene panels and provide comments.

Will the gene panels change?

Gene panels may change over time as knowledge accumulates and curators become aware of new evidence. This includes the addition of new genes, rating changes to existing genes or gene information. The panels may also be merged or split as appropriate. Each change to a panel increases the minor version (E.g. Version 1.0 to Version 1.1). Previous versions of a gene panel can be downloaded using the tool available at the bottom of each gene panel page or by querying WebServices.

The PanelApp ‘Activity’ tab (displayed from the PanelApp home page) displays the last 1000 key changes to all panels. The ‘History’ tab for each gene on a gene panel records changes to gene information. Gene reviews are also added with a date-stamp for tracking.

Gene panels <Version 1 are viewable and can be reviewed. Once expert reviews have been collected and evaluated internally by Genomics England Curators, Version 1 of the gene panels are released. Version 2 panels will be launched when significant changes have been made to Version 1 panels.

What is recorded when I make my evaluation?

When you are logged in as a reviewer, any information you enter using the gene evaluation or new gene tool will be recorded. Your reviewer name (made up of your first name, last name and affiliation used when you registered to be a reviewer) will be attached to ratings and evaluations. To encourage openness, all gene evaluations and comments you make as a reviewer will be open for anyone to see (the public and other reviewers). The date, time and version of the panel when these actions were carried out is also recorded.

Am I able to change my reviewer evaluations?

As a reviewer, you can log in to PanelApp using your log in details, and view and/or edit your evaluations at any time. To make changes to your evaluations, see Section 4.6 of the PanelApp Handbook V5.7.

We expect PanelApp will still be available to be utilised in between gene panel major version releases in order to collect information. We would also be very appreciative of being contacted regarding important evidence related to gene panels (please contact the curation team at Genomics England: panelapp@genomicsengland.co.uk).

Who will be assessing the evaluations?

The evaluations will be viewed by Genomics England Curators using internally established rules and in consultation with Genomics England clinicians.

How will reviews be assessed/conflicting reviews resolved?

A set of rules has been established to define different scenarios in order to have a pragmatic review evaluation process. The Validation & Feedback GeCIP (Genomics England Clinical Interpretation Partners) Domain was involved in establishing this process. Comments regarding changes to gene ratings are viewable in PanelApp for transparency.

Can I send the link to others so that they can review/download panels?

Please distribute the PanelApp URL or gene panel URLs to those within the Scientific Community; anyone can view and download the gene panels. We also encourage those with expertise to register as reviewers.

Please note; if someone else logs in with your review log in details, any evaluations made will over-ride yours, and comments will not be distinguished as being from more than one user. You are therefore responsible for any changes and comments made under your reviewer name.

When I register as a reviewer, where are my details kept and who has access?

Information added during the registration process are stored internally and only utilised for uses related to PanelApp, it will not be passed to third parties. Your first name, last name, affiliation, workplace and group will be visible to the public. Role is collected in order in order to assess reviewer’s backgrounds and may be used to display the demographics of PanelApp reviewers.

You can view your account information by clicking on the “Logged in as: …” button in the top right hand corner of the screen. Please contact panelapp@genomicsengland.co.uk to make any changes to your user information.

Where can I keep up to date with major changes or news regarding PanelApp?

Go to the PanelApp news page. Alternatively, select the ‘Activity’ page from the top menu for the latest key updates to panels. Follow @GenomicsEngland #PanelApp on Twitter. News items will also be displayed on the Genomics England website – for more information see https://www.genomicsengland.co.uk/about-genomics-england/panelapp/.

Can I submit my own gene panels?

We welcome submission of panels of genes from experts for the rare diseases covered in the 100,000 Genomes Project. We will send you a template form so that we can capture the information in a standardised manner, please email panelapp@genomicsengland.co.uk

This is interim information and has not yet received final approval from Genomics England internal governance processes or NHS England and is therefore potentially subject to change.

Contact

For enquiries related to the PanelApp, to give feedback or suggestions, or to submit pathogenic variant lists (de-identified information), please email:

panelapp@genomicsengland.co.uk

Citing PanelApp

To cite PanelApp, please use: Genomics England PanelApp; https://panelapp.genomicsengland.co.uk (date accessed), and provide the name and version of the gene panel(s) used when applicable.

We are interested in how the community is utilising PanelApp - please let us know by emailing panelapp@genomicsengland.co.uk.

Content

Retired panels

Some gene panels may have been applied for genome analysis and interpretation reports that are now retired and are no longer live in webservices or on the PanelApp UI. To access a previously used panel version, use the panel name or the code and the version number to retrive the correct panel.

An example is the panel for Bilateral microtia (which is retired on PanelApp because it has now been merged into the Deafness and congenital structural abnormalities panel but can be retrieved by webservices using the specific version number):

https://panelapp.genomicsengland.co.uk/WebServices/get_panel/Bilateral microtia/?version=1.4

https://panelapp.genomicsengland.co.uk/WebServices/get_panel/553fa00ebb5a161c1b6faa6e/?version=1.4

A full list of retired version 1 panels and their codes:

Sources of information

The 4 sources used in the initial establishment of gene lists are:

Please see the sources for more information, including disclaimers. Information from these sources (manually collected between January 2015-Aug 2015) includes:

  • Genes.
  • Phenotypes.
  • Mode of inheritance (predominantly from the Illumina TruGenome Predisposition Screen, but also captured from UKGTN information and EMory where available).
  • Transcripts (predominantly from the Illumina TruGenome Predisposition Screen).

Other sources:

Expert list or Expert - the gene was submitted on a list of genes from an expert in the disease area.

Expert Review - genes added by an expert during review of the gene panels.

Literature - the gene was sourced from a peer-reviewed published article.

Eligibility statement prior genetic testing - prior genetic testing required/advised on the Genomics England Eligibility Statement for that disorder.

The databases OMIM, Gene2Phenotype, Orphanet and The NCBI Genetics Home Reference were also used for some phenotype, gene or mode of inheritance information and to aid the curation process.

The HGNC website was used to check gene names in order to establish the correct HGNC-approved symbol. Gene terms used within PanelApp are HGNC approved names.

Links to ClinVar and OMIM gene information are provided within PanelApp to aid evaluation of the evidence for an association between the gene and phenotype.

Transcript information was sourced from Ensembl, and direct links are provided to Ensembl, the CCDS Database, Uniprot and NCBI Nucleotide.

We are requesting reviewers provide PubMed IDs (PMIDs) as a reference to publications.

Glossary

Level 4 title, Level 3 title, Level 2 title

These terms refer to the rare disorder categories and titles e.g. Arrhythmogenic Right Ventricular Cardiomyopathy (level 4 title) is a disease under the cardiomyopathies sub-category (level 3 title), within cardiovascular disorders (level 2 title).

Eligibility statement

Eligibility statements for each of the rare diseases have been written and can be found on the Genomics England website. The aim of the eligibility statements is to provide guidance to clinicians regarding the patients most likely to benefit from the opportunity of diagnostic whole genome sequencing and who are therefore eligible for recruitment into the Genomics England Rare Diseases Programme. Each eligibility statement has been informed by at least one clinician specialising in the field and represents a significant effort on the part of the rare disease clinical community.

Each eligibility statement is includes the following key information: 1. The sub-category (Level 3) and disease (Level 4) titles. 2. Inclusion criteria – the clinical features, characteristics or investigations that probands with a given disease must have in order to be eligible for recruitment. 3. Exclusion criteria - the clinical features, characteristics or investigation findings that participants with a given disease must not have in order to be eligible for recruitment. 4. Prior genetic testing – this sets out both in general terms, and where appropriate more specifically, the genetic testing which participants with a given disease must have performed prior to recruitment.

The eligibility statement from version 1.1 (8th May 2015), or from the disorders for fast-track approval version 0.1 document, is provided in the description box for each gene panel. For some gene panels, no eligibility statement is available at the current time. These include disorders within the pilot that were not taken to the main phase of the programme, panels encompassing a broader set of diseases and panels for the cancer programme.

Gene Symbol

The HGNC-approved symbol for the gene from Ensembl release 90.

Gene Name

The HGNC-approved name for the gene from Ensembl release 90.

Gel Status

The number out of the 4 sources that test for this gene for this phenotype. These are also indicated by colour:

  • Green = highest level of confidence; a gene from 3 or 4 sources.
  • Amber = intermediate; a gene from 2 sources.
  • Red = lowest level of confidence; 1 of the 4 sources or from an expert list.

The 4 sources used in the initial establishment of gene lists are mentioned above

Mode of Inheritance

Standardised terms were used to represent the gene-disease mode of inheritance, and were mapped to commonly used terms from the different sources. Below each of the terms is described, along with the equivalent commonly-used terms.

MONOALLELIC, autosomal or pseudoautosomal, not imprinted: A variant on one allele of this gene can cause the disease, and imprinting has not been implicated.

MONOALLELIC, autosomal or pseudoautosomal, maternally imprinted (paternal allele expressed): A variant on the paternally-inherited allele of this gene can cause the disease, if the alternate allele is imprinted (function muted).

MONOALLELIC, autosomal or pseudoautosomal, paternally imprinted (maternal allele expressed): A variant on the maternally-inherited allele of this gene can cause the disease, if the alternate allele is imprinted (function muted).

MONOALLELIC, autosomal or pseudoautosomal, imprinted status unknown: A variant on one allele of this gene can cause the disease. This is the default used for autosomal dominant mode of inheritance where no knowledge of the imprinting status of the gene required to cause the disease is known. Mapped to the following commonly used terms from different sources: autosomal dominant, dominant, AD, DOMINANT.

BIALLELIC, autosomal or pseudoautosomal: A variant on both alleles of this gene is required to cause the disease. Mapped to the following commonly used terms from different sources: autosomal recessive, recessive, AR, RECESSIVE.

BOTH monoallelic and biallelic, autosomal or pseudoautosomal: The disease can be caused by a variant on one or both alleles of this gene. Mapped to the following commonly used terms from different sources: autosomal recessive or autosomal dominant, recessive or dominant, AR/AD, AD/AR, DOMINANT/RECESSIVE, RECESSIVE/DOMINANT.

BOTH monoallelic and biallelic, autosomal or pseudoautosomal (but BIALLELIC mutations cause a more SEVERE disease form), autosomal or pseudoautosomal: A variant on one allele of this gene can cause the disease, however a variant on both alleles of this gene can result in a more severe form of the disease/phenotype.

X-LINKED: hemizygous mutation in males, biallelic mutations in females: A variant in this gene can cause the disease in males as they have one X-chromosome allele, whereas a variant on both X-chromosome alleles is required to cause the disease in females. Mapped to the following commonly used term from different sources: X-linked recessive, XLR, hemizygous.

X linked: hemizygous mutation in males, monoallelic mutations in females may cause disease (may be less severe, later onset than males): A variant in this gene can cause the disease in males as they have one X-chromosome allele. A variant on one allele of this gene may also cause the disease in females, though the disease/phenotype may be less severe and may have a later-onset than is seen in males. X-linked inactivation and mosaicism in different tissues complicate whether a female presents with the disease, and can change over their lifetime. This term is the default setting used for X-linked genes, where it is not known definitately whether females require a variant on each allele of this gene in order to be affected. Mapped to the following commonly used terms from different sources: X-linked dominant, XLD, x-linked, X-LINKED, X-linked.

MITOCHONDRIAL: The gene is in the mitochondrial genome and variants within this can cause this disease, maternally inherited. Mapped to the following commonly used term from different sources: Mitochondrial.

Unknown: Mapped to the following commonly used terms from different sources: Unknown, NA, information not provided.

Other - please specify in evaluation comments: For example, if the mode of inheritance is digenic, please indicate this in the comments and which other gene is involved.

Phenotypes

Phenotypes collected from the sources are provided where possible. Where multiple phenotypes for the gene were listed, it may be that only the top phenoype was captured or only the relevant phenotype for the gene panel was collected. Phenotypes may also be sourced from PanelApp reviewers, OMIM or gene2phenotype during curation of gene panels.

OMIM

A link to the gene page on OMIM is provided to give reviewers quick access to gene-disease information.

ClinVar Variants

A link to the gene page on Clinvar is provided for quick access to information regarding variants within the gene that are associated with different conditions.

Penetrance

This is set as a default to "complete". Please provide information regarding the penetrance in the Comments box in the Evaluate Gene tool.

Publications

Publications that provide evidence linking this gene to this disorder.

Mode of Pathogenicity

For each gene in a gene panel in PanelApp, it is assumed that loss-of-function variants in this gene can cause the disease/phenotype unless an exception to this rule is known. In the PanelApp, we would like to collect information regarding exceptions to this rule. An example of an exception is the PCSK9 gene, where loss-of-function variants are not relevant for a hypercholesterolemic phenotype as they are associated with increased LDL-cholesterol uptake via LDLR PMID: 25911073.

In the PanelApp, we classify loss-of-function variants as those with the following Sequence Ontology (SO) terms: transcript ablation, splice acceptor variant, splice donor variant, stop gained, frameshift variant, stop lost, initiator codon variant/start lost.

SO Terms and descriptions

Sourced from Ensembl:

transcript ablation: A feature ablation whereby the deleted region includes a transcript feature (SO:0001893)

splice acceptor variant: A splice variant that changes the 2 base region at the 3' end of an intron (SO:0001574)

splice donor variant: A splice variant that changes the 2 base region at the 5' end of an intron (SO:0001575)

stop gained: A sequence variant whereby at least one base of a codon is changed, resulting in a premature stop codon, leading to a shortened transcript (SO:0001587)

frameshift variant: A sequence variant which causes a disruption of the translational reading frame, because the number of nucleotides inserted or deleted is not a multiple of three (SO:0001589)

stop lost: A sequence variant where at least one base of the terminator codon (stop) is changed, resulting in an elongated transcript (SO:0001578)

initiator codon variant: A codon variant that changes at least one base of the first codon of a transcript/start lost: a codon variant that changes at least one base of the canonical start codon (SO:0001582)

This gene appears in other panels

A list of other gene panels within PanelApp that contain this gene.

Rating Summary

A summary of the ratings by different reviewers for the level of evidence for this gene to be included on this panel.

Gene History

A record of when the gene was added to the panel in PanelApp and additional key changes to information regarding the gene.

Current diagnostic

This is a checkbox for reviewers available in the Evaluate Gene tool to indicate whether or not they report variants in the gene as part of current diagnostic practice. If you are submitting an evaluation on behalf of a clinical laboratory and you report variants within the gene as part of your current diagnostic practice, please check the box.

Tags

Are attached to genes within a gene panel by a curator. Tags highlight useful information about a gene or gene variants that may affect gene ratings or be useful for future curation. Tags are specific to a gene within a given panel. List of tags and descriptions