What is MetaDome?
MetaDome is a fast and easy-to-use web server that offers an easily
accessible and unique perspective that enables researchers and
clinicians to interpret variants of unknown significance via
'meta-domains'; a concept that we have previously validated
L. Wiel et al. Human Mutation, 2017
) which makes use of protein
domain homology within the human genome to transfer genetic variant
information across homologous domains. MetaDome can visualize
meta-domain information and gene-wide profiles of genetic tolerance.
How can I use MetaDome?
Analyses through MetaDome can be performed by querying a gene name
and desired transcript. The result is a visualization that a user
may interact with to highlight positions of their interest and
obtain more detailed information of those positions. This includes
regional tolerance to missense variation and the presence or absence
of variation at corresponding positions within homologous domains.
To get more familiar with the using MetaDome and all of it's functionality
we strongly advise to
start the tour
Can I use my smartphone or tablet to access MetaDome?
Although we recommend using a laptop/desktop with a compatible
browser for the best user experience, we designed the user interface
to be useable for mobile devices as well. If you encounter any problems or
see any possible improvements please
What desktop browsers are compatible for MetaDome?
The MetaDome web server is developed and extensively tested using
Google Chrome and
recommend using one of these browsers to access all functionality.
Here is a list of compatible and tested browsers:
||Ubuntu 16.04 and 18.04
||7 and 10
I have ran into a problem with MetaDome, what can I do?
Although we have extensively tested MetaDome and are constantly monitoring
the server for any downtime. If you do encounter problems or behaviour you
did not expect. We would highly appreciate it if you could
On what data are the results in MetaDome based?
MetaDome combines data from various public resources. The underlying data
of MetaDome currently contains information from 56,319 human transcripts
protein domain instances, 12,164,292 population-based genetic variants from
, and 34,076 pathogenic mutations from
How often is the underlying data updated?
Currently MetaDome requires a manual reannotation of the underlying data.
In a future version of MetaDome is expected to schedule automatic downloading
of new data releases and automatic reannotation.
Is MetaDome still under construction?
MetaDome is final for its first release version. But we are still actively
attempting to improve MetaDome based on feedback. If you have any improvement
ideas, please contact us
Current improvements that we are working on may be found
Why can I not select my gene / transcript for analysis?
For sake of high data quality we have limited the possible transcripts and genes
suitable for a MetaDome Analysis to the GENCODE
Basic transcripts of which the translation is identically matched with a
sequence. All GENCODE Basic transcripts are validated to be expressed as mRNA
and all SwissProt proteins are curated by experts.
I cannot find the domain that should be in my gene of interest?
All annotated protein domains in MetaDome result from
Pfam holds a strict notion on what a protein domain is and differs to
other protein domain annotation services. We have specifically chose Pfam,
as the underlying method is suitable to indicate homologously identical
positions across protein domains that can directly be used to transfer variant
Why are there black boxes in the meta-domain landscape?
The black boxes represent positions that cannot be aligned to the Pfam
domain consensus. For these positions we
cannot transfer variant information across homologous domains.
How is the tolerance landscape computed?
The tolerance is computed as a from missense over synonymous
variant count ratio, which is calculated in a sliding window manner to
provide a per-position indication of regional tolerance to missense variation.
The variants are based on gnomAD and corrected for codon composition.
For more information we suggest reading
tolerance and generating a tolerance landscape"
What do the tolerance landscape' colours indicate?
The colours are based on missense over synonymous ratio computations
over the entire protein for all proteins. Here the Yellow (or neutral)
is based on the average missense over synonymous ratio score that you
would obtain this way and the red (intolerant) and blue (tolerant) are
based on the top/bottom scores.
For meta-domain information in the positional information, what does the alignment coverage mean?
This corresponds to how many homologous positions are aligned to that
specific position. In general we would advise to maintain a minimum of
80% alignment coverage for high quality results.