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Advanced Computational Methods for CNV Detection in Bacterial Genomes
Jugas, Robin ; Bystrý, Vojtěch (referee) ; Šafránek,, David (referee) ; Vítková, Helena (advisor)
Hlavní pozornost v oblasti strukturálních variací je zaměřena na lidské genomy. Detekce změny variace počtu kopií (CNV) u bakterií je tedy méně rozvinutou oblastí. Běžně používané metody detekce CNV neberou v úvahu specifika bakteriálních kruhových genomů a obecně existuje prostor pro zlepšení metrik výkonnosti. Tato práce představuje metodu detekce CNV nazvanou CNproScan zaměřenou na bakteriální genomy. CNproScan implementuje hybridní přístup kombinující signály hloubky čtení a párů čtení. Bere v potaz všechny vlastnosti bakterií a využívá pouze sekvenační data. Na základě výsledků ze srovnání dosáhl CNproScan velmi dobrých výsledků v různých podmínkách. Pomocí informací z párových čtení jsou CNV klasifikovány do několika kategorií. Ve srovnání s jinými metodami může CNproScan také detekovat mnohem kratší CNV. Vzhledem k nutnosti slučovat nejen signály různých přístupů, ale také výsledky různých algoritmů, dizertační práce také představuje pipelinu nazvanou ProcaryaSV vyvinutou k detekci CNV s využitim pěti nástrojů a slučování jejich výsledků. ProcaryaSV se stará o celý postup od kontroly kvality čtení, ořezávání konců čtení, zarovnání čtení až k detekci CNV.
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CNV detection in the sequencing data
Pleskačová, Barbora ; Škutková, Helena (referee) ; Jugas, Robin (advisor)
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.
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CNV detection in bacterial genomes
Lacinová, Michaela ; Sedlář, Karel (referee) ; Škutková, Helena (advisor)
This master thesis deals with analysis of structural variation of genome and with methods of its sequencing across all generations. Subsequently it contains a description of copy number variation and methods of its detection. The experimental part focuses on algorithm proposal for CNV detection according analysis and testing of uneven coverage in genome, variable representation of GC content and distance of sequence reads. Finally, the algorithm for detecting copy number variation is tested on genomic data of bacteria Klebsiella pneumoniae.
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Morphological and Genomic Profiling of Circulating Tumor Cells in Metastatic Colorectal Cancer
Thiele, Jana-Aletta ; Pitule, Pavel (advisor) ; Mohelníková Duchoňová, Beatrice (referee) ; Kasimir-Bauer, Sabine (referee)
Colorectal cancer (CRC) is the third most common cancer worldwide; it is responsible for nearly 10% of all newly diagnosed cancers and is the second most cause of cancer related death in Europe. Biomarkers for therapy guidance, targeted therapy and survival prognosis are still limited. As CRC is a heterogeneous disease, different parts of the tumor might have varying molecular characteristics which may change during therapy or disease progression. Through solid biopsies and screenings, these local or temporal differences are impossible to monitor. To facilitate detection of these possible temporal changes, a regularly and non-invasively accessible biomarker is required for disease monitoring. Circulating tumor cells (CTCs) might represent such a biomarker as they have been shown to be fluid surrogates of the solid tumor. EpCAM positive CTCs have shown to be prognostic in CRC for survival, but their full potential has not yet been evaluated further. By using the High Definition Single Cell Analysis (HD-SCA) workflow, we were able to analyze the entire spectrum of CTCs and categorize them as the regular CTCs (HD-CTC), CTCs with a smaller nuclear area (CTC-Small), CTCs with low expression of epithelial marker cytokeratin (CTC-LowCK) and CTCs undergoing apoptosis and therefore releasing cell free DNA...
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CNV detection in the sequencing data
Pleskačová, Barbora ; Škutková, Helena (referee) ; Jugas, Robin (advisor)
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.
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CNV detection in bacterial genomes
Lacinová, Michaela ; Sedlář, Karel (referee) ; Škutková, Helena (advisor)
This master thesis deals with analysis of structural variation of genome and with methods of its sequencing across all generations. Subsequently it contains a description of copy number variation and methods of its detection. The experimental part focuses on algorithm proposal for CNV detection according analysis and testing of uneven coverage in genome, variable representation of GC content and distance of sequence reads. Finally, the algorithm for detecting copy number variation is tested on genomic data of bacteria Klebsiella pneumoniae.
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Morphological and Genomic Profiling of Circulating Tumor Cells in Metastatic Colorectal Cancer
Thiele, Jana-Aletta ; Pitule, Pavel (advisor) ; Mohelníková Duchoňová, Beatrice (referee) ; Kasimir-Bauer, Sabine (referee)
Colorectal cancer (CRC) is the third most common cancer worldwide; it is responsible for nearly 10% of all newly diagnosed cancers and is the second most cause of cancer related death in Europe. Biomarkers for therapy guidance, targeted therapy and survival prognosis are still limited. As CRC is a heterogeneous disease, different parts of the tumor might have varying molecular characteristics which may change during therapy or disease progression. Through solid biopsies and screenings, these local or temporal differences are impossible to monitor. To facilitate detection of these possible temporal changes, a regularly and non-invasively accessible biomarker is required for disease monitoring. Circulating tumor cells (CTCs) might represent such a biomarker as they have been shown to be fluid surrogates of the solid tumor. EpCAM positive CTCs have shown to be prognostic in CRC for survival, but their full potential has not yet been evaluated further. By using the High Definition Single Cell Analysis (HD-SCA) workflow, we were able to analyze the entire spectrum of CTCs and categorize them as the regular CTCs (HD-CTC), CTCs with a smaller nuclear area (CTC-Small), CTCs with low expression of epithelial marker cytokeratin (CTC-LowCK) and CTCs undergoing apoptosis and therefore releasing cell free DNA...
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