Recognition of Copy Number Variations in Human Genomes
Thesis Type | Master |
Thesis Status |
Finished
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Student | Florian Haider, Thomas Kluckner |
Final |
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Start |
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Thesis Supervisor | |
External Supervisor |
Dr. Anita Brandstätter
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Contact |
This cooperation between the research group “Databases and Information Systems” (DBIS) from the University of Innsbruck and the Division for Genetic Epidemiology of the Innsbruck Medical University focuses on the implementation of an algorithm for locating copy number variations in the human genome. Copy number variations (CNVs) represent a new kind of genetic variability and are manifested in either deletions or duplications of certain gene regions. Apart from single nucleotide polymorphisms (SNPs) and environmental factors, CNVs are an important factor in the emergence of complex diseases. CNVs can be recognized by regarding certain patterns in the intensity data of the genotypes from the Affymetrics 500K SNP array. The focus in this master thesis lies on implementing the mathematical procedures for CNV recognition on one hand and on the other hand on developing a database application which can handle the huge data amount. At the same time, these procedures should be optimized. The database has to be able to read in and store the data sets for each patient, run the algorithms for CNV detection and finally output the regions with the highest probability for CNVs. An efficient CNV detection software would be of wide interest and could lead to a substantial progress within the field of research for the causes of complex human diseases