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Dashboard pro hodnocení výsledků metatranskriptomické analýzy nástroji bioBakery
Hýl, Jan ; Jurečková, Kateřina (oponent) ; Bartoň, Vojtěch (vedoucí práce)
Metatranskriptomická analýza poskytuje informaci o právě exprimovaných genech organismu v době odebrání analyzovaného vzorku. Rozmach zkoumání genů přišel s vývojem sekvenačních technologií a technologickým pokrokem. Tato práce pojednává o nukleových kyselinách a jejich významu v genetice. Zabývá se pojmy metatranskriptom, metagenom a mikrobiom. Popisuje metodu sekvenování od značky Illumina a představuje software vhodný pro metatranskriptomickou analýzu. Následně práce zahrnuje vytvoření testovacího datasetu, vytvoření dashboardu pro vizualizaci dat a vyzkoušení tohoto dashboardu na testovacím datasetu.
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Metagenomic analysis of animal gut microbioma based on diet
Spanakis, Martin Nikolaos ; Čejková, Darina (oponent) ; Bartoň, Vojtěch (vedoucí práce)
This bachelor’s thesis deals with the sequencing of the microbiome and its composi- tion. It focuses on the gut microbiome of animals, which differs among animals with different diets. The work describes theoretical knowledge about metagenomic analysis of the microbiome, such as sampling procedures, various sequencing methods and data processing. The practical part of the work includes the preparation of the dataset, which includes the collection of data and their preparation for the following metagenomic anal- ysis. The result of the work is the taxonomic classification of bacterial species in the samples and the analysis of their diversity according to the type of diet of individual animals.
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Methods for fast sequence comparison and identification in metagenomic data
Kupková, Kristýna ; Škutková, Helena (oponent) ; Sedlář, Karel (vedoucí práce)
The objective of this thesis is to create a method for identification of organisms in metagenomic data. Until this point methods based on sequence alignment with reference database have been sufficient for this purpose. However, the volume of data grows rapidly with evolvement of sequencing techniques and the alignment-based methods became inconvenient due to computationally demanding alignment. A new technique is introduced in this master’s thesis, which allows alignment-free metagenomic data classification. The method is based on transformation of sequences to genomic signals in form of phase representation, from which feature vectors are extracted. These features are three Hjorth descriptors, which are then subjected expectation maximization for Gaussian mixture model method allowing reliable binning of metagenomic data.
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Ecology of Gemmatimonadota
MUJAKIĆ, Izabela
Phylum Gemmatimonadota is a common group present in many natural environments. Yet, this interesting bacterial group is rarely studied. Since its discovery 20 years ago, only six cultured species have been described. Abundances of Gemmatimonadota in various environments are usually low (<1%), with the exception of soils, where they are one of the more abundant phyla. Probably for this reason, at the onset of this work, most of the knowledge about Gemmatimonadota came from studies of soil environments, while information about their ecology in freshwater lakes was missing. An interesting discovery relating to the unexplored diversity of Gemmatimonadota in freshwaters was the isolation of the first phototrophic member of this group, Gemmatimonas phototrophica, which was cultured from a shallow freshwater lake. To learn more about the ecology of Gemmatimonadota in freshwaters, the main focus of this thesis was the analysis of their distribution and diversity in several freshwater lakes, with emphasis on presence of photoheterotrophic Gemmatimonadota. The potential ecological roles of this group, metabolic capabilities and general genomic characteristics have also been addressed, thereby allowing a broader scope comparison with Gemmatimonadota from other environments such as soil, marine waters, or wastewaters.
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Metagenomic analysis of animal gut microbioma based on diet
Spanakis, Martin ; Čejková, Darina (oponent) ; Bartoň, Vojtěch (vedoucí práce)
This bachelor’s thesis deals with the sequencing of the microbiome and its composi- tion. It focuses on the gut microbiome of animals, which differs among animals with different diets. The work describes theoretical knowledge about metagenomic analysis of the microbiome, such as sampling procedures, various sequencing methods and data processing. The practical part of the work includes the preparation of the dataset, which includes the collection of data and their preparation for the following metagenomic anal- ysis. The result of the work is the taxonomic classification of bacterial species in the samples and the analysis of their diversity according to the type of diet of individual animals.
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Metagenomická analýza vývoje střevního mikrobiomu dětí
Zourková, Tereza ; Škutková, Helena (oponent) ; Bartoň, Vojtěch (vedoucí práce)
Práce pojednává o vlivu metagenomu na vývoj dítěte a o důvodech přínosnosti zkoumání následků změn lidského střevního mikrobiomu. Následně je v práci nastíněna obecná problematika mikrobiomu a historie jeho studií. Také je zde popsáno složení lidského mikrobiomu střev a souvislosti s imunitním systémem nebo například produkcí hormonů. Rovněž práce obsahuje informace o vybraných metodách analýzy metagenomu, konkrétně mikroskopické metody využívající předchozí kultivaci, hmotnostní spektrometrie a metody sekvenační. Je zde popsán také postup analýzy dat pomocí dostupných bioinformatických nástrojů, kterými byla data vhodně předzpracována. Takto vyfiltrovaná data byla připravena pro navazující profilaci metagenomu, která je v práci podrobně popsána. Na závěr práce jsou vyhodnoceny výsledky profilace, na základě kterých jsou odhadnuty průběhy změn mikrobiomu během vývoje dítěte, což je hlavním cílem této bakalářské práce.
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Alignment-free Visualization of Metagenomic Data by Genomic Signal Processing
Kupková, Kristýna
Alignment-free visualization of metagenomic data without prior knowledge about organism composition is one of the major issues in metagenomic bioinformatics. Such a visualization method must place fragments from one organism in close proximity to each other, be reproducible and with rapidly increasing amount of data also work ideally in linear time. A novel technique fulfilling all of these requirements is introduced in this paper. The method is based on transformation of genomic sequence into phase signal representation with extraction of three Hjorth’s descriptors forming three dimensional space for visualization.
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Methods for fast sequence comparison and identification in metagenomic data
Kupková, Kristýna ; Škutková, Helena (oponent) ; Sedlář, Karel (vedoucí práce)
The objective of this thesis is to create a method for identification of organisms in metagenomic data. Until this point methods based on sequence alignment with reference database have been sufficient for this purpose. However, the volume of data grows rapidly with evolvement of sequencing techniques and the alignment-based methods became inconvenient due to computationally demanding alignment. A new technique is introduced in this master’s thesis, which allows alignment-free metagenomic data classification. The method is based on transformation of sequences to genomic signals in form of phase representation, from which feature vectors are extracted. These features are three Hjorth descriptors, which are then subjected expectation maximization for Gaussian mixture model method allowing reliable binning of metagenomic data.
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