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Localization of Methylation Sites in Transposons
Kmeť, Miroslav ; Martínek, Tomáš (referee) ; Vogel, Ivan (advisor)
This master's thesis deals with the creation of a tool for the extraction of methylation level from transposon sequences. Transposons are DNA elements with ability to move or copy themselves and their activity is regulated by DNA methylation. Sequence methylation information is stored in the bisulfite data and their processing is done with parts of two existing tools in a combination with implemented modules. Created tool takes into consideration unique challenges brought in the methylation calling process by transposable elements and it's functionality is presented on a set of experiments with simulated and real data.
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Classification of Small Noncoding RNAs
Žigárdi, Tomáš ; Martínek, Tomáš (referee) ; Vogel, Ivan (advisor)
This masters's thesis contains description of designed and implemented tool for classification of plant microRNA without genome. Properties of mature and star sequences in microRNA duplexes are used. Implemented method is based on clustering of RNA sequences (with CD-HIT) to mainly reduce their count. Selected representants from each clusters are classified using support vector machine. Performance of classification is more than 96% (based on cross-validation method using the training data).
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Detection of chimeras in amplicon sequencing
Heřmánková, Kristýna ; Jurečková, Kateřina (referee) ; Sedlář, Karel (advisor)
Chimeric sequences are the most common artifacts that can occur in sequencing data after the sample amplification using the polymerase chain reaction. The presence of these artifacts can negatively affect results of the analysis. Therefore, the detection and subsequent filtration of chimeric sequences is an important step in the computational processing of sequencing data. This work deals with the principle of chimera formation and the possibility of reducing their occurrence. The aim of this work is to implement an algorithm for chimeras detection in R language and testing its accuracy on data provided by the Veterinary Research Institute in Brno.
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qPCR diagnostika střevního prvoka \kur{Blastocystis} sp. v souboru vzorků od zdravých lidí
ŠLOUFOVÁ, Martina
The main aim of this study was to introduce and optimize the qPCR diagnostic protocol for detection of intestinal protist, Blastocystis sp. We compared the sensitivity of conventional PCR (cPCR) and real-time PCR (qPCR) in a set of 288 human samples from gut-healthy individuals and subtype diversity as detected by Next-generation sequencing (NGS) versus Sanger sequencing. The overall prevalence of Blastocystis sp. was 29 %. Based on the results, we found out that qPCR is a more sensitive method than cPCR. In subtype detection, NGS was completely in agreement with Sanger sequencing but showed higher sensitivity for mixed subtype colonization within one host. A combination of these two approaches could be beneficial for future epidemiological studies.
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Detection of chimeras in amplicon sequencing
Heřmánková, Kristýna ; Jurečková, Kateřina (referee) ; Sedlář, Karel (advisor)
Chimeric sequences are the most common artifacts that can occur in sequencing data after the sample amplification using the polymerase chain reaction. The presence of these artifacts can negatively affect results of the analysis. Therefore, the detection and subsequent filtration of chimeric sequences is an important step in the computational processing of sequencing data. This work deals with the principle of chimera formation and the possibility of reducing their occurrence. The aim of this work is to implement an algorithm for chimeras detection in R language and testing its accuracy on data provided by the Veterinary Research Institute in Brno.
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Application of Hyb-Seq method for reconstruction of reticulate infrageneric phylogeny: example from polyploid genus Curcuma L. (Zingiberaceae)
Skopalíková, Jana ; Fér, Tomáš (advisor) ; Krak, Karol (referee)
This master thesis focuses on the phylogeny of hybridogenous and polyploid genus Curcuma from family Zingiberaceae using Next-Generation Sequencing data from hundreds to thousands nuclear loci. This approach seems to be better than widely used cpDNA and ITS sequencing especially in the case of hybridogenous and polyploid groups. Data for phylogeny reconstruction were generated using Hybridization-based sequencing (Hyb-Seq) method which combines target enrichment and genome skimming strategies. Data analysis was performed primarily using pipeline HybPhyloMaker especially created for Hyb-Seq data analysis. Twenty-seven species from the genus Curcuma and three outgroup species were sequenced in this work. Phylogenetic trees based on all 1 154 and 811 selected nuclear low- copy genes show high support values of all nodes which is in contrast to plastome and rDNA phylogeny with lower support values in some nodes and incongruences in topology compared to low-copy genes phylogeny. Phylogenetic networks inferred from low-copy genes, lineage movement analysis and monophyly tests agree with published hypotheses of interlineage hybrid origin of three species - C. vamana, C. myanmarensis and C. roscoeana. These analyzes show likely hybrid origin of C. candida too with parents from the group Curcuma I and basal...
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Localization of Methylation Sites in Transposons
Kmeť, Miroslav ; Martínek, Tomáš (referee) ; Vogel, Ivan (advisor)
This master's thesis deals with the creation of a tool for the extraction of methylation level from transposon sequences. Transposons are DNA elements with ability to move or copy themselves and their activity is regulated by DNA methylation. Sequence methylation information is stored in the bisulfite data and their processing is done with parts of two existing tools in a combination with implemented modules. Created tool takes into consideration unique challenges brought in the methylation calling process by transposable elements and it's functionality is presented on a set of experiments with simulated and real data.
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|
|
Classification of Small Noncoding RNAs
Žigárdi, Tomáš ; Martínek, Tomáš (referee) ; Vogel, Ivan (advisor)
This masters's thesis contains description of designed and implemented tool for classification of plant microRNA without genome. Properties of mature and star sequences in microRNA duplexes are used. Implemented method is based on clustering of RNA sequences (with CD-HIT) to mainly reduce their count. Selected representants from each clusters are classified using support vector machine. Performance of classification is more than 96% (based on cross-validation method using the training data).
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