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STAIRS: Data reduction strategy on genomics
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
2019 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Background. An enormous accumulation of genomic data has been taking place over the last ten years. This makes the activities of visualization and manual inspection, key steps in trying to understand large datasets containing DNA sequences with millions of letters. This situation has created a gap between data complexity and qualified personnel due to the need of trading between visualization, reduction capacity and exploratory functions, features rarely achieved by existing tools, such as SRA toolkit (https://www.ncbi.nlm.nih.gov/sra/docs/toolkitsoft/), for instance. A novel approach to the problem of genomic analysis and visualization was pursued in this project, by means of STrAtified Interspersed Reduction Structures (STAIRS). Result. Ten weeks of intense work resulted in novel algorithms to compress data, transform it into stairs vectors and align them. Smith–Waterman and Needleman–Wunsch algorithms have been specially modified for this purpose and the application brought about statistical performance and behavioural charts.

Place, publisher, year, edition, pages
2019. , p. 15
Keywords [en]
Waterman, Needleman, Alignment, Topology, Statistics, Functional, Mathematics, Microbiology, genomics, bacillus, frequency, analysis
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:uu:diva-383465OAI: oai:DiVA.org:uu-383465DiVA, id: diva2:1316093
External cooperation
Statens Veterinärmedicinska Anstalt - SVA
Subject / course
Computer Systems Sciences
Educational program
Master Programme in Bioinformatics
Presentation
2019-03-01, A10, Husargatan, 752 37, Uppsala, 13:00 (English)
Supervisors
Available from: 2019-05-16 Created: 2019-05-15 Last updated: 2019-05-16Bibliographically approved

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