Welcome to PanelApp Australia
NEW panel alert: Speech Apraxia
Childhood apraxia of speech (CAS; synonymous with speech apraxia/dyspraxia or verbal apraxia/dyspraxia) is a non-progressive neurodevelopmental disorder with a primary presentation of speech planning and programming disorder.
'Genetic architecture of childhood speech disorder: a review' by AT Morgan, DJ Amor, MD St John, IE Scheffer, and M Hildebrand, Mol Psychiatry 2024, 29(5): 1281-1292 (PMID: 38366112) summarises three gene discovery cohort studies of individuals with CAS. Diagnostic yield ranged between 26-42% and forms the basis of the panel.
With special thanks to Angela Morgan, Michael Hildebrand, Thomas Scerri, David Amor and team for the development of our newest panel!
What is PanelApp?
PanelApp is a publicly available knowledge base 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, providing an opportunity for the standardisation of gene panels, and a consensus on which genes have sufficient evidence for disease association.
PanelApp Australia is an instance of PanelApp deployed by Australian Genomics and contains panels used by Australian diagnostic laboratories, clinicians and researchers, including those used in Australian Genomics and Melbourne Genomics flagship projects. The diagnostic grade ‘Green’ genes in the PanelApp virtual gene panels are used in analysis and reporting by diagnostic laboratories.
We are extremely grateful to the Genomics England PanelApp team, in particular Ellen McDonagh, Antonio Rueda-Martin, Oleg Gerasimenko and Augusto Rendon for making the PanelApp code open source and for their help in deploying this instance.
Find out more about PanelApp
PanelApp crowdsources expert knowledge to establish consensus diagnostic gene panels. Martin AR, Williams E, Foulger RE, Leigh S, Daugherty LC, Niblock O, Leong IUS, Smith KR, Gerasimenko O, Haraldsdottir E, Thomas E, Scott RH, Baple E, Tucci A, Brittain H, de Burca A, Ibañez K, Kasperaviciute D, Smedley D, Caulfield M, Rendon A, McDonagh EM. Nat Genet. 2019 Nov;51(11):1560-1565
Read the PanelApp Handbook (version 7.0)
Read the PanelApp Australia Reviewer's Guide
Watch PanelApp Videos
Use your Google account and sign in to be a reviewer
Query the PanelApp API is available here - for a demo download our recorded webinar here
PanelApp Australia News
HOT OFF THE PRESS: two new publications
New publication in Genetics in Medicine:
'Towards robust clinical genome interpretation: developing consistent terminology to characterise Mendelian disease-gene relationships - allelic requirement, inheritance modes and disease mechanisms'
Roberts AM, DiStefano MT, Riggs ER, Josephs KS, Alkuraya FS, Amberger J, Amin M, Berg JS, Cunningham F, Eilbeck K, Firth HV, Foreman J, Hamosh A, Hay E, Leigh S, Martin CL, McDonagh EM, Perrett D, Ramos EM, Robinson PN, Rath A, Sant DW, Stark Z, Whiffin N, Rehm HL, Ware JS.
PanelApp Australia is a member of the the GenCC together with other organisations that provide online resources (e.g. ClinGen, DECIPHER, Genomics England PanelApp, OMIM, Orphanet, TGMI’s G2P), as well diagnostic laboratories committed to sharing their internal curated gene-level knowledge (e.g. Ambry, Illumina, Invitae, Myriad Women’s Health, Mass General Brigham Laboratory for Molecular Medicine).
The GenCC (http://search.thegencc.org) database provides information pertaining to the validity of gene-disease relationships, with a current focus on Mendelian diseases. Curated gene-disease relationships are submitted by GenCC member organisations.
Through this international collaboration, we hope to accelerate the establishment of a robust evidence base for gene-disease relationships and improve diagnostic outcomes of genomic testing and are currently in the process of identifying and resolving discrepant gene-disease assertions with other submitters.
Here, the GenCC presents a standardised terminology to describe gene-disease relationships, and to support variant annotation. This includes allelic requirement, inheritance modes and disease mechanisms. The consensus terms have been formalised in both sequence ontology (SO) and human phenotype ontology (HPO).
New publication in Genetics in Medicine Open:
'Evolution of virtual gene panels over time and implications for genomic data re-analysis'
Robertson AJ, Tran K, Patel C, Sullivan C, Stark Z and Waddell N
This publication explores how the content of 112 rare disease panels in PanelApp Australia evolved between 2019 and 2022. This revealed large volumes of change both in genes being added, upgraded and downgraded on genes reflecting activities to align panels nationally and internationally as well as to keep them up-to-date with new knowledge.
New publication in Genetics in Medicine:
'The Gene Curation Coalition: A global effort to harmonize gene-disease evidence resources'
DiStefano MT, Goehringer S, Babb L, Alkuraya FS, Amberger J, Amin M, Austin-Tse C, Balzotti M, Berg JS, Birney E, Bocchini C, Bruford EA, Coffey AJ, Collins H, Cunningham F, Daugherty LC, Einhorn Y, Firth HV, Fitzpatrick DR, Foulger RE, Goldstein J, Hamosh A, Hurles MR, Leigh SE, Leong IUS, Maddirevula S, Martin CL, McDonagh EM, Olry A, Puzriakova A, Radtke K, Ramos EM, Rath A, Riggs ER, Roberts AM, Rodwell C, Snow C, Stark Z, Tahiliani J, Tweedie S, Ware JS, Weller P, Williams E, Wright CF, Yates TM, Rehm HL.
PanelApp Australia is a member of the the GenCC together with other organisations that provide online resources (e.g. ClinGen, DECIPHER, Genomics England PanelApp, OMIM, Orphanet, TGMI’s G2P), as well diagnostic laboratories committed to sharing their internal curated gene-level knowledge (e.g. Ambry, Illumina, Invitae, Myriad Women’s Health, Mass General Brigham Laboratory for Molecular Medicine).
The GenCC (http://search.thegencc.org) database provides information pertaining to the validity of gene-disease relationships, with a current focus on Mendelian diseases. Curated gene-disease relationships are submitted by GenCC member organisations.
Through this international collaboration, we hope to accelerate the establishment of a robust evidence base for gene-disease relationships and improve diagnostic outcomes of genomic testing and are currently in the process of identifying and resolving discrepant gene-disease assertions with other submitters.
Gene Curation Coalition website launch!
We are thrilled to announce the launch of the Gene Curation Coalition (GenCC) Database (DB) on the GenCC website (http://search.thegencc.org). The GenCC DB provides information pertaining to the validity of gene-disease relationships, with a current focus on Mendelian diseases. Curated gene-disease relationships are submitted by GenCC member organisations.
PanelApp Australia is a member of the the GenCC together with other organisations that provide online resources (e.g. ClinGen, DECIPHER, Genomics England PanelApp, OMIM, Orphanet, TGMI’s G2P), as well diagnostic laboratories committed to sharing their internal curated gene-level knowledge (e.g. Ambry, Illumina, Invitae, Myriad Women’s Health, Mass General Brigham Laboratory for Molecular Medicine).
Member groups submit assertions about gene-disease relationships. Each entry is an assertion for a gene, a disease, and a mode of inheritance, including, or linked to, evidence supporting that assertion. Different displays within the database show assertions by submitter, by disease, by gene, and by clinical validity level. All data is downloadable for public use, though OMIM data must be separately accessed through OMIM.org.
At launch, the database contains 3552 gene-disease assertions on 2222 unique genes from eight different groups, with many more to come! Through this international collaboration, we hope to accelerate the establishment of a robust evidence base for gene-disease relationships and improve diagnostic outcomes of genomic testing.
Panel comparison and harmonisation with Genomics England PanelApp complete!
We have now completed comparing ALL 80 panel pairs that cover the same clinical indications in the Genomics England and Australian PanelApp instances!
The two curation teams exchanged more than 2,000 gene reviews to resolve discrepancies and harmonise content. We hope the changes translate to more diagnoses and greater efficiency.
A MASSIVE THANK YOU to everyone who took part and helped us improve!
We will be presenting this work at the 2020 HGSA Virtual Conference on Tuesday 24th November
Rare Disease panels: time for the November update!
We update the rare disease panels every month so that the latest research discoveries are translated into diagnostic benefits for patients and families as quickly as possible.
The teams at the Victorian Clinical Genetics Services, the Royal Melbourne Hospital and Genetic Health Queensland are systematically reviewing recent journal issues and we are combining our efforts with the Genomics England PanelApp curator team.
Hot off the press: a bumper crop this month, we have just added 55 new gene-disease associations!
Rare Disease panels: time for the October update!
We update the rare disease panels every month so that the latest research discoveries are translated into diagnostic benefits for patients and families as quickly as possible.
The teams at the Victorian Clinical Genetics Services, the Royal Melbourne Hospital and Genetic Health Queensland are systematically reviewing recent journal issues and we are combining our efforts with the Genomics England PanelApp curator team.
Hot off the press: 35 new gene-disease associations added this month!
Have you published a new gene-disease association? Or seen one that we are still missing?
Help us add them: log in as a reviewer and add them to at least one panel! We will do the rest.
Not sure how to do it? Follow the instructions in the Reviewers tab or contact us panelapp@australiangenomics.org.au
Mackenzie's Mission Reproductive Carrier Screening panel is now on PanelApp Australia
Mackenzie's Mission will provide reproductive carrier screening to 10,000 Australian couples. Congratulations to the Mackenzie's Mission team on their recent publication in the European Journal of Human Genetics, describing the process of gene selection.
Gene selection for the Australian Reproductive Genetic Carrier Screening Project ("Mackenzie's Mission")
Kirk EP, Ong R, Boggs K, Hardy T, Righetti S, Kamien B, Roscioli T, Amor DJ, Bakshi M, Chung CWT, Colley A, Jamieson RV, Liebelt J, Ma A, Pachter N, Rajagopalan S, Ravine A, Wilson M, Caruana J, Casella R, Davis M, Edwards S, Archibald A, McGaughran J, Newson AJ, Laing NG, Delatycki MB. Eur J Hum Genet, 2020 Jul 16, epub ahead of print
July Rare Disease panel update results:
20 journal issues reviewed, 29 new gene-disease associations added.
A huge thank you to the teams at the Victorian Clinical Genetics Services, the Royal Melbourne Hospital, Genetic Health Queensland and Genomics England PanelApp for doing the literature review together and helping to translate research into immediate diagnostic benefit for patients and families.
Rare Disease panels June update!
We are moving to monthly rare disease panel updates so that we can quickly translate the latest research discoveries into diagnostic benefits for patients and families.
The teams at the Victorian Clinical Genetics Services, the Royal Melbourne Hospital and Genetic Health Queensland are systematically reviewing recent journal issues this week and we are combining our efforts with the Genomics England PanelApp curator team.
Have you come across a recent new gene-disease association that we are still missing? Help us find them: log in as a reviewer and add them to at least one panel! We will do the rest. Not sure how to do it? Follow the instructions in the Reviewers tab or contact us panelapp@australiangenomics.org.au
Rare Disease panels update!
We have just completed a major literature review and update of our Rare Disease panels! Thank you to the teams at the Victorian Clinical Genetics Services and the Royal Melbourne Hospital for reviewing 101 journal issues, and adding 58 new genes over the past week -- we hope this translates to many more diagnoses for families.
Can you see any new genes we are still missing? Help us find them!
Register as a reviewer, add them to the most appropriate panel and we will take care of the rest. Not sure how? Follow the instructions in the Reviewers tab or contact us panelapp@australiangenomics.org.au
Maintenance Announcement! 11th February 2020
Please note: PanelApp Australia site will be unavailable from 11-02-2020 Tuesday between 15:00 - 17:00 (AEDT) for updating release version 3.1.1. We apologise for any inconvenience this may cause. This release will include changes to the signed off panel API endpoint to display panel count and pagination.
Panel Swap! 21st January 2020
It's Panel Swap time! Over the next few weeks, you will notice PanelApp Australia panels appearing in Genomics England PanelApp and vice versa! We are swapping panels to enable systematic comparison and resolution of discrepancies, starting with renal disease, epilepsy, intellectual disability and hearing loss panels. Through this process, we hope to build consensus internationally and improve the evidence base for diagnostic practice in rare disease genomics.
Maintenance Announcement! 8th January 2020
As part of performance improvement, PanelApp Australia site is scheduled down for maintenance update from 19:00 AEST 2019-01-08.
We will follow up with another announcement, once it is back to operational. During this period, you may see 503 Service Unavailable.
PanelApp Australia is now officially LIVE! 17th December 2019
We have been working closely with the Genomics England PanelApp Team to deploy a local instance of PanelApp to make the sharing of information about gene-disease associations between Australian laboratories, clinicians and researchers more efficient. This has been made possible through the partnerships that Australian Genomics and Genomics England have built as Driver Projects under the Global Alliance for Genomics and Health.
The open nature of PanelApp allows the crowdsourcing of contributions from many experts, facilitating timely identification of newly published evidence regarding gene-disease associations.
PanelApp was designed by Genomics England for the 100,000 Genomes project, and now the platform is being used to reach a consensus in gene panel content for genetic tests in the NHS Genomic Medicine Service.
PanelApp Australia already contains 185 virtual gene panels from Australian Genomics flagship projects, Melbourne Genomics flagship projects, the KidGen Collaborative, the Victorian Clinical Genetics Services, Genetic Health Queensland and the University of Melbourne's Centre for Cancer Research (UMCCR).
We plan to use the platform to build consensus nationally and contribute to international efforts to establish gene-disease relationships. Future co-development of the platform will include connection between the two instances of PanelApp to facilitate knowledge transfer between Genomics England and Australian Genomics, as well as extending PanelApp Australia for somatic cancer panel use.
We would like to thank the team at Genomics England: Ellen McDonagh, Antonio Rueda-Martin, Oleg Gerasimenko and Augusto Rendon for making the PanelApp code open source, and for their help in deploying this instance, and to all those who have helped in the development of the PanelApp software.
We would also like to thank A/Prof Oliver Hofmann's Genomics Platform Group at UMCCR who have been responsible for the technical deployment of PanelApp Australia and A/Prof Zornitza Stark at Australian Genomics/VCGS for coordinating content management.
Release notice 17th November 2019
PanelApp Australia will be upgraded to v3.0.2 from 9am - 12pm (AEST) on 17th November. PanelApp will not be accessible during this time.
PanelApp publication out! 1st November 2019
Read the Genomics England PanelApp team new publication PanelApp crowdsources expert knowledge to establish consensus diagnostic gene panels
Nat Genet (2019) doi:10.1038/s41588-019-0528-2
Antonio Rueda Martin and Eleanor Williams, Rebecca E. Foulger, Sarah Leigh, Louise C. Daugherty, Olivia Niblock, Ivone U. S. Leong, Katherine R. Smith, Oleg Gerasimenko, Eik Haraldsdottir, Ellen Thomas, Richard H. Scott, Emma Baple, Arianna Tucci, Helen Brittain, Anna de Burca, Kristina Ibañez, Dalia Kasperaviciute, Damian Smedley, Mark Caulfield, Augusto Rendon & Ellen M. McDonagh
PanelApp Reviewers
PanelApp has a crowdsourcing review tool to allow each gene to be reviewed and commented on by experts within the scientific community. To become a reviewer, you will need your nominated Google account for PanelApp Australia panels reviewing purpose. If you already have one ready in mind, please login here using your Google account. If you do not have a Google account (prefer not to use your existing one), click 'create account' on the screen, and then select 'use my current email address' on the following screen to sign up new Google account for PanelApp Australia reviewing purpose.
Please see Reviewer Login section below for further login steps and troubleshooting.
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 and to help keep diagnostic panels keep up to date with new gene discoveries.
Read the PanelApp Australia Reviewer's guide. This will take you through the entire review process, through to leaving a review on a panel.
Desired reviewer experience
- Reviewers can have an academic, clinical and/or diagnostic laboratory background.
- Reviewers can be based anywhere in the world.
In order to encourage expert review of the gene panels, we would request that reviewers of the gene panels should have:
- Expertise in the relevant disease area, genes or in diagnostic genetic testing.
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 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.
- Add gene panels.
What are we asking of reviewers?
- Rate the genes and genomic entities on a panel as Green (high evidence for gene-disease association, variants in this gene reportable in the diagnostic setting) or Red (low evidence for gene-disease association). If the evidence is not fully conclusive, please rate as Amber (borderline), Please read the criteria for the evidence level required on the Guidelines tab.
- Provide supporting evidence for your rating, including Publications and Phenotypes.
- Add missing genes to a gene panel.
How to make a review
Read information about PanelApp
You can find out more about PanelApp from the PanelApp homepage, including about the role of expert reviewers and gene panel guidelines.
Find gene panels
To find the gene panel(s) 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 "renal", the list will be filtered to display all panels related to renal disease.
Review the genes in the gene panel
Click on a gene in the panel and provide a review using the ‘Reviews’ tab (see picture below)
Please leave feedback for each gene on a panel, specifically:
Provide a rating
Provide a gene rating ( Green (high evidence for gene-disease association, variants in this gene reportable in the diagnostic setting) or Red (low evidence for gene-disease association)). 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 Free-text justifications in the comments box to support your rating.
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.
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 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.
An example of an exception to the rule are the genes causing Rasopathies.
Provide additional information to support your review
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. Include full references and attributions to sources of information for your review.
Add genes to the Panel
Add any missing genes using the tool found at the bottom of the entity list on the panel (pictured). Provide a rating for the new gene. New genes should be rated Green 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).
Note that new genes will be added to the panel as 'Grey' until reviewed by a PanelApp Australia curator.
How to view your evaluations
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.
When re-visiting PanelApp, click on your username in the top right hand corner of the PanelApp home page 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.
Considerations when reviewing
- Information for genes on the Red list will still be maintained for future reference. As more evidence emerges, these may be promoted to the Green list.
- 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.
Reviewer Login
If you have a Google account, you can login to PanelApp Australia!
- In summary, PanelApp Australia delegate user authentication mechanism to your Google account.
- Since PanelApp Australia is designed for crowd source reviewing tool, this simplify the process of some typical website sign up flow such as Sign Up > Wait > Verify Your Email > Approve routine. Instead, PanelApp Australia fast track this by delegating authenticity to your Google account.
- Upon your login, PanelApp Australia site maintaining team receive notification and, may (or may not) further apply any user authorisation mechanism within PanelApp system to your Google account.
Login Steps
Step 1
- When you try to log in as a reviewer or clicking "Login" on PanelApp Australia page, you will be redirected to Google login page as follows.
- At this point, if you already have Google account in mind to use for PanelApp Australia reviewing purpose, you can simply use your nominated Google account login to proceed.
- If your organisation has Google GSuite institution domain setup, you are encouraged to use this work-related GSuite Google account at this point. (Please check with your IT administrator.)
- Otherwise, click "Create account" to proceed Step 2.
Please note that "Sign in to continue to amazoncognito.com" is legitimate message as PanelApp Australia use Amazon Cognito technology as Single-Sign-On (SSO) solution behind the scene. We will be improving this screen message in future.
Step 2
- By clicking "Create account" bring you the following screen.
- If you like to create a new Google account that end with some.username@gmail.com then you can proceed fill up form, First name, Last name and Username to complete creating new Google user account. And use this account for PanelApp Australia panel reviewing purpose.
- However, if you like to affiliate with your institution existing email address, click "Use my current email address instead" to proceed to Step 3.
Step 3
- By clicking "Use my current email address instead" bring you the following screen.
- This process allow you to use your existing email to create a Google account as described in https://support.google.com/accounts/answer/27441
401 Authorization Required messages
Please note your Google account need to be filled your given name (first name) and family name (last name). Please see https://support.google.com/accounts/answer/27442 for instruction. Otherwise, you will encounter "401 Authorization Required messages" during login/register attempt. PanelApp site needs your name info to show Reviewer Name purpose. See Microcephaly panel for how this name info is showed for example. It is recommended to have your first name and last name entered properly as this translates your review contribution to a panel.
Login Troubleshooting
If you try to log in as a reviewer and still having issue on Google login page is not showing up then please try the following troubleshooting steps.
Solution 1
- Open new browser window tab
- Go to address https://www.google.com
- Click on your user avatar (top right corner) and click "Sign out of all accounts"
- Make sure you have log out of all Google accounts and, had seen as follows:
- And try to log in as a reviewer again
Solution 2
- Try with different browser
Solution 3
- Try with browser in "Private Window or Incognito Window" mode
PanelApp Gene Panel Guidelines
How to rate the genes: Rare Disease
Green (diagnostic-grade) genes 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 testing category for which the panel is intended. (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.
Gene Panel Principles for Rare Diseases
- The Green genes on a panel should be a conservative (diagnostic-grade) set of genes that out of the whole exome/genome should be examined first as variants within these genes are most likely to cause/explain the disease phenotype.
- We acknowledge that the panel 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 them to enter use in a diagnostic setting.
- 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 continuously as we learn from newly published evidence.
PanelApp API
PanelApp Frequently Asked Questions
Why gene panels?
Pre-curated virtual gene panels increase the efficiency of genomic data analysis and reporting by targeting analysis to the genes most relevant to the presenting phenotype, and those with well established gene-disease relationships.
How is PanelApp Australia different to the Genomics England PanelApp?
PanelApp Australia contains virtual gene panels from Australian diagnostic laboratories, clinicians and research groups, including the gene panels used by Australian Genomics and Melbourne Genomics flagship projects. The laboratory or other entity responsible for curating and maintaining the panel is indicated in the panel name.
We hope to use the platform to enable national consensus to be reached on gene panels in specific areas, as well as to increase the efficiency of panel curation through shared effort.
We work closely with the Genomics England PanelApp team, and hope to enable data sharing between the two platforms, further accelerating international consensus on gene panels.
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 different clinical indications, as well as help keep panels up-to-date in view of new gene discoveries.
Can experts not in Australia be a reviewer?
Yes! This is an open platform and we would like to encourage those with expertise in specific 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.
As an expert reviewer, how do I rate the genes?
Green Genes included in a diagnostic panel should fit the criteria A-E outlined on the Guidelines tab.
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 by diagnostic laboratories and may contribute to the diagnosis of patients. The gene panels are publicly 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 will continue to change over time as knowledge accumulates and curators become aware of new evidence. The panels may also be merged or split as appropriate, and Super panels may be created made up of two or more child panels. Each change to a panel increases the minor version (E.g. Version 1.0 to Version 1.1). If substantial changes to a gene panel are made, a Cuator may increase the gene panel to the next major version (E.g. Version 1.115 to Version 2.0).
Note that Version 1.10 of a gene panel is more recent than Version 1.2, because each minor curation change to the panel increases the minor version incrementally. Think of it instead like Version 1_10 and Version 1_2.
Previous versions of a gene panel can be downloaded using the tool available at the bottom of each gene panel page or by querying API.
The PanelApp ‘Activity’ tab (displayed from the PanelApp home page) displays the last 3000 key changes to all panels. This can be filtered using the filter icon (funnel) to select the panel or date you would like to view. Filter this further by typing in the 'Filter activities' box.
The ‘History’ tab for each gene or genomic entity on a gene panel records changes to gene/entity information. Gene reviews are also added with a date-stamp for tracking.
The 'Panel Activity' tool button at the bottom of the panel description box displays all changes for thiat panel.
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.
Who will be assessing the evaluations?
The evaluations will be viewed by the Curators of each laboratory that maintains the panel.
How will reviews be assessed/conflicting reviews resolved?
Conflicting reviews will be resolved by the curator team. 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 and affiliation will be visible to the public.
You can view your account information by clicking on your user name in the top right hand corner of the screen.
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.
Citing PanelApp
To cite PanelApp, please use:
PanelApp crowdsources expert knowledge to establish consensus diagnostic gene panels. Antonio Rueda Martin and Eleanor Williams, Rebecca E. Foulger, Sarah Leigh, Louise C. Daugherty, Olivia Niblock, Ivone U. S. Leong, Katherine R. Smith, Oleg Gerasimenko, Eik Haraldsdottir, Ellen Thomas, Richard H. Scott, Emma Baple, Arianna Tucci, Helen Brittain, Anna de Burca, Kristina Ibañez, Dalia Kasperaviciute, Damian Smedley, Mark Caulfield, Augusto Rendon & Ellen M. McDonagh. Nat Genet (2019) doi:10.1038/s41588-019-0528-2
Where applicable, please provide the name and version of the gene panel(s).
Acknowledgements
We are extremely grateful to the Genomics England PanelApp team, in particular Ellen McDonagh, Antonio Rueda-Martin, Oleg Gerasimenko and Augusto Rendon for making the PanelApp code open source and for their help in deploying the Australian instance.
Link outs from PanelApp
Links to ClinVar from gene pages are provided. Reference: Landrum M.J. et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 44(D1):D862-8. (2016).
Links to Gene2Phenotype from gene pages are provided. References: Wright CF et al. Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data. Lancet. 385(9975):1305-14. (2015), The Development Disorder Genotype - Phenotype Database.
Links to OMIM from gene pages are provided.
Links are provided to Ensembl Build 37 and Build 38 from gene pages. Reference: Zerbino DR et al. Ensembl 2018. Nucleic Acids Res. 46(D1):D754-D761. (2018).
PanelApp Glossary
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.
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 definitely 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 phenotype 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.
OMIM SYMBOLS
Brackets, "[ ]" indicate "nondiseases," mainly genetic variations that lead to apparently abnormal laboratory test values (e.g., dysalbuminemic euthyroidal hyperthyroxinemia).
Braces, "{ }" indicate mutations that contribute to susceptibility to multifactorial disorders (e.g., diabetes, asthma) or to susceptibility to infection (e.g., malaria).
A question mark, "?" before the phenotype name indicates that the relationship between the phenotype and gene is provisional. More details about this relationship are provided in the comment field of the map and in the gene and phenotype OMIM entries.
The number in parentheses after the name of each disorder indicates the following: (1) the disorder was positioned by mapping of the wildtype gene; (2) the disease phenotype itself was mapped; (3) the molecular basis of the disorder is known; (4) the disorder is a chromosome deletion or duplication syndrome. Move the cursor over the number to display this 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/Genomic Entity History
A record of when the gene or genomic entity (a STR or CNV) was added to the panel in PanelApp and additional key changes to gene or entity information.
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 a gene or genomic entity 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. A list of tags and descriptions is available here.