Copy number variation detection in prokaryotic organisms is currently receiving more and more attention, mainly due to the association of CNV with pathogenicity and antibiotic resistance in bacteria. The algorithm designed in this thesis uses peak detection in sequencing coverage to detect CNV segments. Read coverage is commonly obtained by mapping sequencing reads of one individual to an already known reference of another individual of the same species. However, two individuals will always differ in a certain number of genes, resulting in unmapped reads that are unnecessarily discarded. Therefore, this work assumes that the biological accuracy of CNV detection can be increased by using a new reference that is created from the same set of reads as the reads mapped to this reference. Sequencing reads of Klebsiella pneumoniae individuals are used to verify this assertion.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:413021 |
| Date | January 2020 |
| Creators | Pleskačová, Barbora |
| Contributors | Škutková, Helena, Jugas, Robin |
| Publisher | Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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