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Open Access
Peer-reviewed
Research Article
A geographically matched control population efficiently limits the number of candidate disease-causing variants in an unbiased whole-genome analysis
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Matilda Rentoft ,
Contributed equally to this work with: Matilda Rentoft, Daniel Svensson, Andreas Sjödin
Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing
Affiliations Department of Medical Biochemistry and Biophysics, Umeå University, SE Umeå, Sweden, Computational Life Science Cluster, Department of Chemistry, Umeå University, SE Umeå, Sweden
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Daniel Svensson ,
Contributed equally to this work with: Matilda Rentoft, Daniel Svensson, Andreas Sjödin
Roles Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing
Affiliation Computational Life Science Cluster, Department of Chemistry, Umeå University, SE Umeå, Sweden
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Andreas Sjödin ,
Contributed equally to this work with: Matilda Rentoft, Daniel Svensson, Andreas Sjödin
Roles Formal analysis, Investigation, Methodology, Supervision, Validation, Writing – review & editing
Affiliations Computational Life Science Cluster, Department of Chemistry, Umeå University, SE Umeå, Sweden, Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, SE Umeå, Sweden
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Pall I. Olason,
Roles Data curation, Formal analysis, Methodology, Validation, Writing – review & editing
Affiliation Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, SE Uppsala, Sweden
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Olle Sjöström,
Roles Data curation, Formal analysis, Investigation, Writing – review & editing
Affiliations Department of Radiation Sciences, Oncology, Umeå University, SE Umeå, Sweden, Unit of research, education and development, Region Jämtland Härjedalen, SE Östersund, Sweden
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Carin Nylander,
Roles Project administration, Resources, Writing – review & editing
Affiliation Department of Radiation Sciences, Oncology, Umeå University, SE Umeå, Sweden
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Pia Osterman,
Roles Formal analysis, Investigation, Validation, Writing – review & editing
Affiliation Department of Medical Biochemistry and Biophysics, Umeå University, SE Umeå, Sweden
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Rickard Sjögren,
Roles Software, Writing – review & editing
Affiliation Computational Life Science Cluster, Department of Chemistry, Umeå University, SE Umeå, Sweden
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Sergiu Netotea,
Roles Software
Affiliations Computational Life Science Cluster, Department of Chemistry, Umeå University, SE Umeå, Sweden, Science for Life Laboratory, Department of Biology and Biological Engineering, Chalmers University of Technology, SE Göteborg, Sweden
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Carl Wibom,
Roles Data curation, Investigation, Writing – review & editing
Affiliation Department of Radiation Sciences, Oncology, Umeå University, SE Umeå, Sweden
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Kristina Cederquist,
Roles Resources, Writing – review & editing
Affiliation Department of Medical Biosciences, Medical and Clinical Genetics, Umeå University, SE Umeå, Sweden
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Andrei Chabes,
Roles Conceptualization, Funding acquisition, Writing – review & editing
Affiliation Department of Medical Biochemistry and Biophysics, Umeå University, SE Umeå, Sweden
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Johan Trygg,
Roles Funding acquisition, Supervision, Validation, Writing – review & editing
Affiliation Computational Life Science Cluster, Department of Chemistry, Umeå University, SE Umeå, Sweden
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Beatrice S. Melin ,
Roles Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing
¶‡ These authors also contributed equally to this work.
Affiliation Department of Radiation Sciences, Oncology, Umeå University, SE Umeå, Sweden
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Erik Johansson
Roles Conceptualization, Funding acquisition, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing
* E-mail: erik.tm.johansson@umu.se
¶‡ These authors also contributed equally to this work.
Affiliation Department of Medical Biochemistry and Biophysics, Umeå University, SE Umeå, Sweden
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A geographically matched control population efficiently limits the number of candidate disease-causing variants in an unbiased whole-genome analysis
- Matilda Rentoft,
- Daniel Svensson,
- Andreas Sjödin,
- Pall I. Olason,
- Olle Sjöström,
- Carin Nylander,
- Pia Osterman,
- Rickard Sjögren,
- Sergiu Netotea,
- Carl Wibom
- Published: March 27, 2019
- https://doi.org/10.1371/journal.pone.0213350