{"entity": "researcher", "timestamp": "2026-09-23T19:00:24.433Z", "family": "Magnusson", "given": "M\u00e5ns", "initials": "M", "orcid": "0000-0002-0001-1047", "affiliations": ["Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology, and Health, KTH Royal Institute of Technology, Stockholm, Sweden. mans.magnusson@scilifelab.se.", "Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden. mans.magnusson@scilifelab.se.", "Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden. mans.magnusson@scilifelab.se."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/42a30865d19844979f57c37b7403f93a.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/42a30865d19844979f57c37b7403f93a"}}, "publications": [{"entity": "publication", "iuid": "a0e03b765e384ea89f57c34fd48a30b4", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/a0e03b765e384ea89f57c34fd48a30b4.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/a0e03b765e384ea89f57c34fd48a30b4"}}, "title": "PatientMatcher: A customizable Python-based open-source tool for matching undiagnosed rare disease patients via the Matchmaker Exchange network.", "authors": [{"family": "Rasi", "given": "Chiara", "initials": "C", "orcid": "0000-0002-7001-3988", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6dde34e53e6d4b6a85914ad12cb6299c.json"}}, {"family": "Nilsson", "given": "Daniel", "initials": "D", "orcid": "0000-0001-5831-385X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/49e071495ddf43e5b570dfb22c1fec06.json"}}, {"family": "Magnusson", "given": "M\u00e5ns", "initials": "M", "orcid": "0000-0002-0001-1047", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/42a30865d19844979f57c37b7403f93a.json"}}, {"family": "Lesko", "given": "Nicole", "initials": "N"}, {"family": "Lagerstedt-Robinson", "given": "Kristina", "initials": "K", "orcid": "0000-0001-9848-0468", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/be7aa52cf290424f8f544a0034a1543a.json"}}, {"family": "Wedell", "given": "Anna", "initials": "A", "orcid": "0000-0002-2612-6301", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/ae9ba593bf3e472fa7d157cd697c7427.json"}}, {"family": "Lindstrand", "given": "Anna", "initials": "A", "orcid": "0000-0003-0806-5602", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3d28fb4cc61f4033b2ac525fed3d6b94.json"}}, {"family": "Wirta", "given": "Valtteri", "initials": "V", "orcid": "0000-0003-3811-5439", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/6a4f538e838c483eb968174f2df89165.json"}}, {"family": "Stranneheim", "given": "Henrik", "initials": "H"}], "type": "journal article", "published": "2022-06-00", "journal": {"title": "Hum. Mutat.", "issn": "1098-1004", "volume": "43", "issue": "6", "pages": "708-716", "issn-l": "1059-7794"}, "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.", "doi": "10.1002/humu.24358", "pmid": "35192731", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC9311682"}], "notes": [], "created": "2026-09-23T12:55:50.429Z", "modified": "2026-09-23T12:55:50.558Z"}, {"entity": "publication", "iuid": "18df53ce886d4472bf6b914d15ea6df5", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/18df53ce886d4472bf6b914d15ea6df5.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/18df53ce886d4472bf6b914d15ea6df5"}}, "title": "Loqusdb: added value of an observations database of local genomic variation.", "authors": [{"family": "Magnusson", "given": "M\u00e5ns", "initials": "M", "orcid": "0000-0002-0001-1047", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/42a30865d19844979f57c37b7403f93a.json"}}, {"family": "Eisfeldt", "given": "Jesper", "initials": "J"}, {"family": "Nilsson", "given": "Daniel", "initials": "D"}, {"family": "Rosenbaum", "given": "Adam", "initials": "A"}, {"family": "Wirta", "given": "Valtteri", "initials": "V"}, {"family": "Lindstrand", "given": "Anna", "initials": "A"}, {"family": "Wedell", "given": "Anna", "initials": "A"}, {"family": "Stranneheim", "given": "Henrik", "initials": "H"}], "type": "journal article", "published": "2020-07-01", "journal": {"title": "BMC Bioinformatics", "issn": "1471-2105", "volume": "21", "issue": "1", "pages": "273", "issn-l": "1471-2105"}, "abstract": "Exome and genome sequencing is becoming the method of choice for rare disease diagnostics. One of the key challenges remaining is distinguishing the disease causing variants from the benign background variation. After analysis and annotation of the sequencing data there are typically thousands of candidate variants requiring further investigation. One of the most effective and least biased ways to reduce this number is to assess the rarity of a variant in any population. Currently, there are a number of reliable sources of information for major population frequencies when considering single nucleotide variants (SNVs) and small insertion and deletions (INDELs), with gnomAD as the most prominent public resource available. However, local variation or frequencies in sub-populations may be underrepresented in these public resources. In contrast, for structural variation (SV), the background frequency in the general population is more or less unknown mostly due to challenges in calling SVs in a consistent way. Keeping track of local variation is one way to overcome these problems and significantly reduce the number of potential disease causing variants retained for manual inspection, both for SNVs and SVs.\n\nHere, we present loqusdb, a tool to solve the challenge of keeping track of any type of variant observations from genome sequencing data. Loqusdb was designed to handle a large flow of samples and unlike other solutions, samples can be added continuously to the database without rebuilding it, facilitating improvements and additions. We assessed the added value of a local observations database using 98 samples annotated with information from a background of 888 unrelated individuals.\n\nWe show both how powerful SV analysis can be when filtering for population frequencies and how the number of apparently rare SNVs/INDELs can be reduced by adding local population information even after annotating the data with other large frequency databases, such as gnomAD. In conclusion, we show that a local frequency database is an attractive, and a necessary addition to the publicly available databases that facilitate the analysis of exome and genome data in a clinical setting.", "doi": "10.1186/s12859-020-03609-z", "pmid": "32611382", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC7329469"}, {"db": "pii", "key": "10.1186/s12859-020-03609-z"}], "notes": [], "created": "2026-09-23T12:02:33.850Z", "modified": "2026-09-23T12:02:33.922Z"}, {"entity": "publication", "iuid": "a0e42f45c0564c7aa2828466e46fbac4", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/a0e42f45c0564c7aa2828466e46fbac4.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/a0e42f45c0564c7aa2828466e46fbac4"}}, "title": "Chanjo: Clincal grade sequence coverage analysis", "authors": [{"family": "Andeer", "given": "Robin", "initials": "R"}, {"family": "Magnusson", "given": "M\u00e5ns", "initials": "M", "orcid": "0000-0002-0001-1047", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/42a30865d19844979f57c37b7403f93a.json"}}, {"family": "Wedell", "given": "Anna", "initials": "A"}, {"family": "Stranneheim", "given": "Henrik", "initials": "H"}], "type": "journal-article", "published": "2020-06-16", "journal": {"title": "F1000Res", "issn": "2046-1402", "volume": "9", "pages": "615", "issn-l": "2046-1402"}, "abstract": null, "doi": "10.12688/f1000research.23605.1", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-09-23T13:12:59.015Z", "modified": "2026-09-23T13:12:59.069Z"}]}