High throughput sequencing provides unprecedented power to detect genetic variation in applications such as inherited disorders and somatic mutations in cancer, but managing and filtering the enormous data sets remains a challenge.
Existing software can annotate variants, predict effects and remove false positives, but ultimately an individual may need to sort through many hundreds of thousands of potential candidates, using expert knowledge of relevant pathways and phenotypes.
Clinicians and researchers often do not know how to program, and existing graphical interfaces do not scale to exome-size data sets. A graphical front end that allows creation of sophisticated custom filters on these large data sets could thus leverage expert knowledge to gain more from exome-scale sequencing.
Our technology stores variant and genotype information in a relational database, with a graphical web front end to display and filter this data.
A drag and drop interface allows a user to connect together nodes that represent filtering operations which are applied to the variants. This allows rapid creation of custom filters and analysis, encourages experimentation and provides a visual summary of operations applied.
Our technology's node graph user interface improves on existing solutions by allowing the construction of sophisticated filters over larger data sets.
This technology will be valuable in the medical field, when a non-expert needs to filter, search and analyse a patient’s genetic variants in a database. Examples of where this technology would be beneficial include: