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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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Bacterial species delineation based on parameters derived from numerical representations of genome
Oweis, Kamil ; Jugas, Robin (referee) ; Maděránková, Denisa (advisor)
Modern methods of processing genomic data yield good results, however they are often redeemed by time consummation. This is mainly the reason why this thesis deals with numerical methods of bacterial genome processing which could be a suitable alternative for current methods, both in terms of quality and computational demands. This thesis presents the current methods used for processing of genomes in silico and proposes suitable numerical presentations for the whole genome analysis. Some of these methods are programmed and used for processing further in this diploma thesis. In it, various mathematical and statistical methods are being tested, ones that could lead to successful species delineation of bacteria by numerical presentations of their genomes.
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Digital processing of plant genomes
Jugas, Robin ; Škutková, Helena (referee) ; Sedlář, Karel (advisor)
This work continues in development of DNA numerical representation’s field in the recent years. The aim of this bachelor thesis is to work out an overview of numerical representations of DNA sequences and to describe the differences and properties of nuclear and mitochondrial genetic code focused on plants. Final objective is analysis of usability these signal’s representations for classification of organisms. The theoretical part is focused on description of biological facts, overview of conversion methods of DNA sequences into signals, the methods of organisms classification and the DTW algorithm. The practical part contain the created GUI application for organism classification based on numerical sequences and the analysis of usability these numerical representations for classification. The outputs of cluster analysis of numerical sequences are compared with the phylogenetic tree.
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Homology search using digital signal processing methods
Kamar, Yana ; Jugas, Robin (referee) ; Maděránková, Denisa (advisor)
Thesis includes the theoretical introduction to molecular biology and genetics on the necessary level, including a description of the structure of DNA and the homologous gene. Described are fixed and physic-chemical kinds of nucleotide mapping, methods for processing digital signals. Numerical representations of genes that were programmed in MATLAB: unwrapped and accumulated phases, density vectors. Using the unwrapped phase and density vectors with windows of different lengths was performed CDS searching in the entire genome by calculation metric distances (euclidean and canberian) and correlation. Also, using the metric distances, a homologous gene was found in more or less similar bacterial genomes. The result is the approximate threshold of distance (euclidean and canberian) using to find homologous genes in genome.
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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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Evaluation of numerical representations suitability for overlap detection
Pleskačová, Barbora ; Maděránková, Denisa (referee) ; Jugas, Robin (advisor)
The bachelor´s thesis is focused on the evaluation of numerical representations suitability for overlap detection. Introductory part deals with description of deoxyribonucleic acid structure. The next part discribes sequencing methods and genome assembly techniques. Following part deals with numerical representations that convert DNA sequences into numerical form. Based on similarity metrics, the use of these representations is tested for the detection of overlaps between DNA reads. In the practical part of the thesis an algorithm for overlap detection is designed and implemented using numerical representations. The algorithm is then tested on data.
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Direct Binning of Metagenomic Signals from Nanopore Sequencing
Lebó, Marko ; Jugas, Robin (referee) ; Sedlář, Karel (advisor)
This diploma thesis deals with taxonomy independent methods for classification of metagenomic signals, aquired by a MinION sequencer. It describes the formation and character of metagenomic data and already existing methods of metagenomic data classification and their development. This thesis also evaluates an impact of the third generation sequencing techniques in the world of metagenomics and further specialises on the function of the Oxford Nanopore MinION sequencing device. Lastly, a custom method for metagenomic data classification, based on data obtained from a MinION sequencer, is proposed and compared with an already existing method of classification.
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Signal processing based methods for genome assembly refinement
Jugas, Robin ; Provazník, Ivo (referee) ; Sedlář, Karel (advisor)
The diploma thesis deals with sequencing methods and genome assembly methods including usage of numerical representations. The theoretical part of thesis describes the history of DNA research, generations of sequencing methods, the assembly methods themselves and definiton of numerical representations. Numerical represenatations serve to convert character form of DNA to numerical form and so allow to use digital signal processing methods. There is an algorithm for genome assembly using numerical represenatation proposed in thesis, which is later tested at sequence data.
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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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Bacterial species delineation based on parameters derived from numerical representations of genome
Oweis, Kamil ; Jugas, Robin (referee) ; Maděránková, Denisa (advisor)
Modern methods of processing genomic data yield good results, however they are often redeemed by time consummation. This is mainly the reason why this thesis deals with numerical methods of bacterial genome processing which could be a suitable alternative for current methods, both in terms of quality and computational demands. This thesis presents the current methods used for processing of genomes in silico and proposes suitable numerical presentations for the whole genome analysis. Some of these methods are programmed and used for processing further in this diploma thesis. In it, various mathematical and statistical methods are being tested, ones that could lead to successful species delineation of bacteria by numerical presentations of their genomes.
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