In rare genetic diseases, a single genetic alteration can be enough to cause a severe disorder.
Recent advances in genetic research have introduced exome or genome sequencing
into clinical care. However, each sequencing run delivers a myriad of candidate variants
that have to be sifted through in the hunt for the causative mutation - a major data
challenge, for which researchers and clinicians have to rely on computer tools.
With MutationDistiller, we have developed a freely available online tool to analyse whole
exome sequencing data in a user-driven fashion. The tool aims at clinicians and researchers
without bioinformatic experience who are working with real patient data, and
allows them to distil the most likely causative variants from the sea of candidates. By
uploading the patient’s genetic information and adding information on the symptoms,
they can combine genotype and phenotype to find the culprit. MutationDistiller allows a
wide range of phenotype data, such as HPO, OMIM and Orphanet entries, gene panels,
expression data, Gene Ontology terms, and affected pathways. In the output, the program
provides an ordered list of candidate alterations matching the user-defined criteria.
In addition, crucial data on the alteration and the affected gene can be reviewed at a
This thesis describes the program, its background and usage, and compares it to current
state-of-the-art tools. When assessing the tool, we found that it matches or out-competes
similar software and is able to find the causative variant in a majority of cases. Moreover,
its user-friendliness makes it a handy tool for clinicians and researchers, as is reflected
by its usage: MutationDistiller routinely sees over 1,000 cases per month and has been
used in over 14,000 cases at the time of writing. Thus, MutationDistiller has already
found its way into the clinic.
The tool, comprehensive documentation and example cases are freely available at