PAROBKOVÁ, V. Bioinformatická analýza jednonukleotidových polymorfismů v databázi 1000 Genomes Project [online]. Brno: Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. 2020.
Studentka Viktória Parobková si během řešení práce počínala nadstandardně ve všech oblastech hodnocení. Literární rešerše v úvodní části čerpá z více než dostatečného počtu 44 citací, ze kterých jsou informace efektivně včleněny a logicky uspořádány do textu. Daná problematika je psána čtivou formou, navíc v anglickém jazyce. Jádro práce - bioinformatická analýza byla provedena za účelem objevení knock-outů genů vyskytujících se přirozeně v populacích. Skóre reziduální variace netolerance bylo vyčísleno pro odhad genů, které jsou vysoce tolerantní k mutaci a naopak. Studentkou provedené analýzy jednotlivých genových oblastí jsou stručně, ale jasně popsány. Výsledky analýz jsou vhodným způsobem graficky prezentovány. Celý text svědčí o výborném zvládnutí netriviálního multioborového zadání. Vypracování celé práce bylo pečlivé a samostatné, se zájmem o rešeršní i analytickou činnost, s pravidelnými konzultacemi dílčích výsledků. Zadání považuji za splněné, práci doporučuji k obhajobě.
The current work by Viktória Parobková is an aim to study the human genome variations. There are 2 parts of the project. The first part explains successfully “The International HapMap project” and “The 1000 Genomes Project”. Both the projects are associated with the whole genome sequencing and variant discovery. The main emphasis is to study the whole genome mapping of DNA variations, and the genomic structural variants studied by allele frequencies and correlation patterns. The second part of the thesis provides the variant data produced by phase 3 of the 1000 Genomes Project. Statistical, population and bioinformatic analyses were run on data to show population stratification, gene-knockouts, relationships among populations and the amounts of homozygous and heterozygous deletions within individuals. The text of the thesis is comprised of 59 pages plus appendices and contains a list of 44 completely relevant references. Formally, the work is very well done, the structure and editing of the text is fully acceptable. Some sections contain typos and placement of the figures are not uniform in parts. Overall, the Figures and Tables are self-explanatory and supports the research findings. The Introduction portion is very well drafted, and it connects very well with the subsequent topics. From a professional point of view, the work is very well designed, it contains all the necessary parts. I especially appreciate the brief but concise description of the Genetics and the individual sequencing methods and the properties of the data they provide. The chapter 4 about the "The 1000 Genomes Project" is very well drafted. The pilot project which includes details about "Variant Calling and its novelty is very well explained. The author describes about the details of "A typical Genome" and provides information about African ancestry that exhibits most of the variant sites. This is an important statement. The detailing of the variant sites under the observation would throw more light into the subject. Similar informative findings were provided under the " Putatively functional variation section". There is an information that states that " The European population had most of the variants per genome that were linked with a disease (around 2000) and rare diseases. More data added under this subject will streamline the disease based research. The population genetic property and functional impact of structural variants is very well explained and is quite informative. “East Asia exhibited the highest levels of homozygous deletions” and “More than 80% of these homozygous gene loses were novel comparing with previous studies”. The statement provides valuable information in the context of Gene mapping and simultaneously integrating phylogenetics, phylogeography and population. The analysis of DNA variation data underlies and summarizes the software analysis of variation data from the 1000 Genomes project. The implementation was done in a programming language named R, and the structural variant studies were presented by bioinformatic, statistical and population analyses. The results are informative in terms of diversification of a population and its stratification. “On average, the highest levels of SV-homozygosity were exhibited by East Asian populations with around 430 homozygous events and the lowest by African populations with only 230 events”. This is a vital piece of information. The bioinformatic analysis was performed on homozygous deletion to discover gene knock-outs occurring naturally in populations. RVIS (Residual Variation Intolerance Score) were calculated for genes to deduce the genes that are highly tolerant to mutation and vice versa. The analysis on UTR3/5 and CDS regions are very well explained with proper graphical depiction. I evaluate the work on a very positive index. The findings are informative and appropriate. The scholar worked intensively on the work and I find the results useful for the professionals to work in the area of single nucleotide polymorphisms. The implementation of the output will help researchers to better understand common and rare diseases on a genomic level.
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