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  • 1.
    Karlsson, Edvin
    et al.
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Sullivan, Alexis R.
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences. Umeå University, Faculty of Science and Technology, Umeå Plant Science Centre (UPSC).
    Svensson, Daniel
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Bellieny-Rabelo, Daniel
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Siddique, Abu Bakar
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Villegas, José Antonio
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Johansson, Anna-Mia
    Umeå University, Faculty of Science and Technology, Department of Molecular Biology (Faculty of Science and Technology).
    Grahn, Håkan
    CBRN skydd och säkerhet, Totalförsvarets forskningsinstitut, FOI.
    Sundell, David
    CBRN skydd och säkerhet, Totalförsvarets forskningsinstitut, FOI.
    Brindefalk, Björn
    Department of Environmental Sciences, Stockholm University, Stockholm, Sweden.
    Norman, Anita
    Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, Sweden.
    Sjödin, Andreas
    CBRN skydd och säkerhet, Totalförsvarets forskningsinstitut, FOI.
    Singh, Navinder J.
    Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, Sweden.
    Brodin, Tomas
    Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, Sweden.
    Forsman, Mats
    CBRN skydd och säkerhet, Totalförsvarets forskningsinstitut, FOI.
    Stenberg, Per
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine). Umeå University, Faculty of Science and Technology, Department of Molecular Biology (Faculty of Science and Technology). Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
    Airborne eDNA captures the diversity and dynamics of a subarctic ecosystem across three decadesManuscript (preprint) (Other academic)
  • 2.
    Rentoft, Matilda
    et al.
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics. Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Svensson, Daniel
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Sjödin, Andreas
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, SE Umeå, Sweden.
    Olason, Pall I.
    Sjöström, Olle
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology. Unit of research, education and development, Region Jämtland Härjedalen, SE Östersund, Sweden.
    Nylander, Carin
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Osterman, Pia
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    Sjögren, Rickard
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Netotea, Sergiu
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Science for Life Laboratory, Department of Biology and Biological Engineering, Chalmers University of Technology, SE Göteborg, Sweden.
    Wibom, Carl
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Cederquist, Kristina
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Medical and Clinical Genetics.
    Chabes, Andrei
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Melin, Beatrice S.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Johansson, Erik
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    A geographically matched control population efficiently limits the number of candidate disease-causing variants in an unbiased whole-genome analysis2019In: PLOS ONE, E-ISSN 1932-6203, Vol. 14, no 3, article id e0213350Article in journal (Refereed)
    Abstract [en]

    Whole-genome sequencing is a promising approach for human autosomal dominant disease studies. However, the vast number of genetic variants observed by this method constitutes a challenge when trying to identify the causal variants. This is often handled by restricting disease studies to the most damaging variants, e.g. those found in coding regions, and overlooking the remaining genetic variation. Such a biased approach explains in part why the genetic causes of many families with dominantly inherited diseases, in spite of being included in whole-genome sequencing studies, are left unsolved today. Here we explore the use of a geographically matched control population to minimize the number of candidate disease-causing variants without excluding variants based on assumptions on genomic position or functional predictions. To exemplify the benefit of the geographically matched control population we apply a typical disease variant filtering strategy in a family with an autosomal dominant form of colorectal cancer. With the use of the geographically matched control population we end up with 26 candidate variants genome wide. This is in contrast to the tens of thousands of candidates left when only making use of available public variant datasets. The effect of the local control population is dual, it (1) reduces the total number of candidate variants shared between affected individuals, and more importantly (2) increases the rate by which the number of candidate variants are reduced as additional affected family members are included in the filtering strategy. We demonstrate that the application of a geographically matched control population effectively limits the number of candidate disease-causing variants and may provide the means by which variants suitable for functional studies are identified genome wide.

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  • 3.
    Sundell, David
    et al.
    CBRN Security and Defence, FOI, Swedish Defence Research Agency, Umeå, Sweden.
    Öhrman, Caroline
    CBRN Security and Defence, FOI, Swedish Defence Research Agency, Umeå, Sweden.
    Svensson, Daniel
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences. CBRN Security and Defence, FOI, Swedish Defence Research Agency, Umeå, Sweden;Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden.
    Karlsson, Edvin
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences. CBRN Security and Defence, FOI, Swedish Defence Research Agency, Umeå, Sweden;Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden.
    Brindefalk, Björn
    CBRN Security and Defence, FOI, Swedish Defence Research Agency, Umeå, Sweden.
    Myrtennäs, Kerstin
    CBRN Security and Defence, FOI, Swedish Defence Research Agency, Umeå, Sweden.
    Ahlinder, Jon
    CBRN Security and Defence, FOI, Swedish Defence Research Agency, Umeå, Sweden.
    Antwerpen, Markus H
    Department of Microbial Genomics and Bioinformatics, Bundeswehr Institute of Microbiology, Munich, Germany.
    Walter, Mathias C
    Department of Microbial Genomics and Bioinformatics, Bundeswehr Institute of Microbiology, Munich, Germany.
    Forsman, Mats
    CBRN Security and Defence, FOI, Swedish Defence Research Agency, Umeå, Sweden.
    Stenberg, Per
    Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences. CBRN Security and Defence, FOI, Swedish Defence Research Agency, Umeå, Sweden;Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden.
    Sjödin, Andreas
    CBRN Security and Defence, FOI, Swedish Defence Research Agency, Umeå, Sweden.
    FlexTaxD: flexible modification of taxonomy databases for improved sequence classification2021In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 37, no 21, p. 3932-3933Article in journal (Refereed)
    Abstract [en]

    The Flexible Taxonomy Database framework provides a method for modification and merging official and custom taxonomic databases to create improved databases. Using such databases will increase accuracy and precision of existing methods to classify sequence reads.

  • 4.
    Svensson, Daniel
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Rentoft, Matilda
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    Dahlin, Anna M.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Lundholm, Emma
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Olason, Pall, I
    Sjödin, Andreas
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Nylander, Carin
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Melin, Beatrice S.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Johansson, Erik
    Umeå University, Faculty of Medicine, Department of Medical Biochemistry and Biophysics.
    A whole-genome sequenced control population in northern Sweden reveals subregional genetic differences2020In: PLOS ONE, E-ISSN 1932-6203, Vol. 15, no 9, article id e0237721Article in journal (Refereed)
    Abstract [en]

    The number of national reference populations that are whole-genome sequenced are rapidly increasing. Partly driving this development is the fact that genetic disease studies benefit from knowing the genetic variation typical for the geographical area of interest. A whole-genome sequenced Swedish national reference population (n = 1000) has been recently published but with few samples from northern Sweden. In the present study we have whole-genome sequenced a control population (n = 300) (ACpop) from Västerbotten County, a sparsely populated region in northern Sweden previously shown to be genetically different from southern Sweden. The aggregated variant frequencies within ACpop are publicly available (DOI 10.17044/NBIS/G000005) to function as a basic resource in clinical genetics and for genetic studies. Our analysis of ACpop, representing approximately 0.11% of the population in Västerbotten, indicates the presence of a genetic substructure within the county. Furthermore, a demographic analysis showed that the population from which samples were drawn was to a large extent geographically stationary, a finding that was corroborated in the genetic analysis down to the level of municipalities. Including ACpop in the reference population when imputing unknown variants in a Västerbotten cohort resulted in a strong increase in the number of high-confidence imputed variants (up to 81% for variants with minor allele frequency < 5%). ACpop was initially designed for cancer disease studies, but the genetic structure within the cohort will be of general interest for all genetic disease studies in northern Sweden.

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  • 5.
    Svensson, Daniel
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Sjögren, Rickard
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Corporate Research, Sartorius AG, Umeå, Sweden.
    Sundell, David
    Sjödin, Andreas
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Corporate Research, Sartorius AG, Umeå, Sweden.
    doepipeline: a systematic approach to optimizing multi-level and multi-step data processing workflows2019In: BMC Bioinformatics, E-ISSN 1471-2105, Vol. 20, no 1, article id 498Article in journal (Refereed)
    Abstract [en]

    Background: Selecting the proper parameter settings for bioinformatic software tools is challenging. Not only will each parameter have an individual effect on the outcome, but there are also potential interaction effects between parameters. Both of these effects may be difficult to predict. To make the situation even more complex, multiple tools may be run in a sequential pipeline where the final output depends on the parameter configuration for each tool in the pipeline. Because of the complexity and difficulty of predicting outcomes, in practice parameters are often left at default settings or set based on personal or peer experience obtained in a trial and error fashion. To allow for the reliable and efficient selection of parameters for bioinformatic pipelines, a systematic approach is needed.

    Results: We present doepipeline, a novel approach to optimizing bioinformatic software parameters, based on core concepts of the Design of Experiments methodology and recent advances in subset designs. Optimal parameter settings are first approximated in a screening phase using a subset design that efficiently spans the entire search space, then optimized in the subsequent phase using response surface designs and OLS modeling. Doepipeline was used to optimize parameters in four use cases; 1) de-novo assembly, 2) scaffolding of a fragmented genome assembly, 3) k-mer taxonomic classification of Oxford Nanopore Technologies MinION reads, and 4) genetic variant calling. In all four cases, doepipeline found parameter settings that produced a better outcome with respect to the characteristic measured when compared to using default values. Our approach is implemented and available in the Python package doepipeline.

    Conclusions: Our proposed methodology provides a systematic and robust framework for optimizing software parameter settings, in contrast to labor- and time-intensive manual parameter tweaking. Implementation in doepipeline makes our methodology accessible and user-friendly, and allows for automatic optimization of tools in a wide range of cases. The source code of doepipeline is available at https://github.com/clicumu/doepipeline and it can be installed through conda-forge.

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  • 6.
    Svensson, Daniel
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden; Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Öhrman, Caroline
    Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Bäckman, Stina
    Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Karlsson, Edvin
    Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Nilsson, Elin
    Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Byström, Mona
    Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Lärkeryd, Adrian
    Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Myrtennäs, Kerstin
    Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Stenberg, Per
    Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Qu, Ping-hua
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden.
    Scholz, Holger C.
    Forsman, Mats
    Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Sjödin, Andreas
    Umeå University, Faculty of Science and Technology, Department of Chemistry. Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden; Division of CBRN Security and Defence, FOI–Swedish Defence Research Agency, Umeå, Sweden.
    Complete Genome Sequence of Francisella guangzhouensis Strain 08HL01032(T), Isolated from Air-Conditioning Systems in China2015In: Microbiology Resource Announcements, E-ISSN 2576-098X, Vol. 3, no 2, article id e00024-15Article in journal (Refereed)
    Abstract [en]

    We present the complete genome sequence of Francisella guangzhouensis strain 08HL01032(T), which consists of one chromosome (1,658,482 bp) and one plasmid ( 3,045 bp) with G+C contents of 32.0% and 28.7%, respectively.

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