ArticleHuman mutation2022
PatientMatcher: A customizable Python-based open-source tool for matching undiagnosed rare disease patients via the Matchmaker Exchange network.
Article in Human mutation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Development, Implementation, and Preliminary Results of a Novel Social Network for Rare Disease Communities: Mixed Methods Study.JMIR human factors · 2026Article
- The genomic medicine center Karolinska 10-year report on genome sequencing for rare diseases and a strategy for stepwise clinical implementation.Genome medicine · 2026Article
- Information content as a health system screening tool for rare diseases.NPJ digital medicine · 2025Article
- Targeted Sequencing Approach and Its Clinical Applications for the Molecular Diagnosis of Human Diseases.Cells · 2023Review
- The impact of GeneMatcher on international data sharing and collaboration.Human mutation · 2022Article
- Seven years since the launch of the Matchmaker Exchange: The evolution of genomic matchmaking.Human mutation · 2022Article
- PatientMatcher: A customizable Python-based open-source tool for matching undiagnosed rare disease patients via the Matchmaker Exchange network.Human mutation · 2022Article
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Authors and funding
9 authors.
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Abstract
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 routine 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.
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