Computational analysis of plasma glycome and genotypes in human populations

Tica, Jelena (2011) Computational analysis of plasma glycome and genotypes in human populations. Diploma thesis, Faculty of Science > Department of Biology.

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Abstract

Clinical diseases are characterized by distinct phenotypes. To identify disease–related genes or to develop appropriate diagnostic tests, it is necessary to elucidate the gene–phenotype relationships. Genome–wide association studies (GWAS) are used for identifying genetic associations with phenotypic traits by analyzing a set of single nucleotide polymorphisms (SNPs) as the genetic markers. SNPs arise from point mutations in DNA and are the major source of diversity among individuals. Phenotypic trait that can be analyzed in a context of genetic changes is glycosylation. This process involves the addition of glycans (sugar chains) to both proteins and lipids, and is the most complex and abundant post-translational modification. The goal of this research is to find the possible relationship between glycosylation profiles and SNPs in isolated human populations by using bioinformatics tools and machine learning algorithms, and to develop an analysis pipeline that would be reproducible and statistically relevant. I have developed a method and a set of computational tools to analyze and visualize correlations between glycans and genotypes based on hierarchical clustering of glycan profile distance data and identity by descent (IBD) values in genotypes. Analysis performed on two distinct datasets from two isolated populations in Croatia and Scotland show that the method is able to identify distinct glycan profiles in subpopulations and find their correlation to genotype results.

Item Type: Thesis (Diploma thesis)
Keywords: glycosylation, GWAS, SNP, bioinformatics, machine learning
Supervisor: Vlahoviček, Kristian
Date: 2011
Number of Pages: 56
Subjects: NATURAL SCIENCES > Biology
Divisions: Faculty of Science > Department of Biology
Depositing User: Grozdana Sirotic
Date Deposited: 10 Jun 2014 08:43
Last Modified: 18 Sep 2014 11:07
URI: http://digre.pmf.unizg.hr/id/eprint/2315

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