PatientMatcher: a customizable Python-based open-source tool for
matching undiagnosed rare disease patients via the MatchMaker Exchange
The amount of data available from genomic medicine has revolutionized
the approach to identify the determinants underlying many rare diseases.
The task of confirming a genotype-phenotype causality for a patient
affected with a rare genetic disease is often challenging. In this
context, the establishment of the MatchMaker Exchange (MME) network has
assumed a pivotal role in bridging heterogeneous patient information
stored on different medical and research servers. MME has made it
possible to solve rare disease cases by “matching” the genotypic and
phenotypic characteristics of a patient of interest with patient data
available at other clinical facilities participating in the network.
Here, we present PatientMatcher
(https://github.com/Clinical-Genomics/patientMatcher), an open-source
Python and MongoDB-based software solution developed by Clinical
Genomics facility at the Science for Life Laboratory in Stockholm.
PatientMatcher is designed as a standalone MME server, but can easily
communicate via REST API with external applications managing genetic
analyses and patient data. The MME node is being implemented in clinical
production in collaboration with the Genomic Medicine Center Karolinska
at the Karolinska University Hospital. PatientMatcher is written to
implement the MME API and provides several customizable settings,
including a custom-fit similarity score algorithm and adjustable
matching results notifications.