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CheckQC: Quick quality control of Illumina sequencing runs
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab. (Ann-Christine Syvänen)ORCID iD: 0000-0002-2450-6415
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab. (Ann-Christine Syvänen)ORCID iD: 0000-0002-8184-9465
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab. (Ann-Christine Syvänen)ORCID iD: 0000-0001-6962-1460
2018 (English)In: Journal of Open Source Software, E-ISSN 2475-9066, Vol. 3, no 22, article id 556Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2018. Vol. 3, no 22, article id 556
Keywords [en]
bioinformatics, sequencing
National Category
Bioinformatics (Computational Biology)
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:uu:diva-349255DOI: 10.21105/joss.00556OAI: oai:DiVA.org:uu-349255DiVA, id: diva2:1200995
Available from: 2018-04-24 Created: 2018-04-24 Last updated: 2022-09-15Bibliographically approved
In thesis
1. Genetic Cartography at Massively Parallel Scale
Open this publication in new window or tab >>Genetic Cartography at Massively Parallel Scale
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Massively parallel sequencing (MPS) is revolutionizing genomics. In this work we use, refine, and develop new tools for the discipline.

MPS has led to the discovery of multiple novel subtypes in Acute Lymphoblastic Leukemia (ALL). In Study I we screen for fusion genes in 134 pediatric ALL patients, including patients without an assigned subtype. In approximately 80% of these patients we detect novel or known fusion gene families, most of which display distinct methylation and expression patterns. This shows the potential for improvements in the clinical stratification of ALL. Large sample sizes are important to detect recurrent somatic variation. In Study II we investigate if a non-index overlapping pooling schema can be used to increase sample size and detect somatic variation. We designed a schema for 172 ALL samples and show that it is possible to use this method to call somatic variants.

Around the globe there are many ongoing and completed genome projects. In Study III we sequenced the genome of 1000 Swedes to create a reference data set for the Swedish population. We identified more than 10 million variants that were not present in publicly available databases, highlighting the need for population-specific resources. Data, and the tools developed during this study, have been made publicly available as a resource for genomics in Sweden and abroad.

The increased amount of sequencing data has created a greater need for automation. In Study IV we present Arteria, a computational automation system for sequencing core facilities. This system has been adopted by multiple facilities and has been used to analyze thousands of samples. In Study V we developed CheckQC, a program that provides automated quality control of Illumina sequencing runs. These tools make scaling up MPS less labour intensive, a key to unlocking the full future potential of genomics.

The tools, and data presented here are a valuable contribution to the scientific community. Collectively they showcase the power of MPS and genomics to bring about new knowledge of human health and disease.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 68
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1492
Keywords
Acute Lymphoblastic Leukemia (ALL), RNA-Sequencing, Bioinformatics, Pooling, Whole Genome Sequencing
National Category
Medical Genetics Cancer and Oncology Hematology Computer Systems Bioinformatics (Computational Biology)
Research subject
Medical Genetics; Bioinformatics
Identifiers
urn:nbn:se:uu:diva-358289 (URN)978-91-513-0428-1 (ISBN)
Public defence
2018-10-19, E10:1307-1309 (Trippelrummet), Navet, Biomedicinskt centrum, Husargatan 3, Uppsala, 09:00 (English)
Opponent
Supervisors
Available from: 2018-09-20 Created: 2018-08-27 Last updated: 2018-10-02

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Åslin, MatildaBrandt, MonikaDahlberg, Johan

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