Fachbereich Informatik - Aktuell

Disputation Alexander Peltzer

am Freitag, 18.05.2018, um 13:00 Uhr Raum A301, Sand 1

Alexander Peltzer

Computational methods for ancient genome reconstruction

Berichterstatter 1: apl. Prof. Dr. Kay Nieselt
Berichterstatter 2: Prof. Dr. Johannes Krause

Kurze Zusammenfassung des Vortrags
Applications of next-generation sequencing (NGS) technologies have become the de facto standard in the systematic analysis of the genetic composition of organisms. Aforementioned is not just valid for modern DNA analysis, but also for ancient DNA (aDNA) where NGS methods have almost entirely replaced PCR-based approaches.
Studying DNA variation in ancient humans provides promising opportunities to unravel missing links in human history that are otherwise hard to detect. While this is encouraging, there are still several issues in analyzing NGS data from ancient specimens, posing challenges to bioinformatics.
The main topic of this dissertation concentrates on the development of EAGER, a framework for the analysis of aDNA data with a variety of use cases and improvements in contrast to previously published methods. EAGER features several newly contributed analysis methods, aiming at recovering as much aDNA as possible from sequencing experiments. Additionally, the pipeline provides an integrated solution to analyze aDNA data in an advanced way, running several state of the art analysis methods to reconstruct ancient genomes. The applicability of EAGER has been demonstrated in various aDNA analysis projects and is further illustrated within this thesis, having been applied to the reconstruction of the genome of George Bähr, the architect of Dresden Frauenkirche, and a total of 90 ancient Egyptian individuals from Abusir El-Meleq in Northern Egypt.
The second part of this thesis furthermore provides a conceptual introduction of MitoBench and MitoDB. The idea of MitoBench centers around the concept of an advanced analysis application that can be used by researchers to integrate their mitochondrial population genetics data with metadata from a variety of resources. In addition, the idea of MitoDB provides a centrally accessible database of mitochondrial DNA with metadata to serve as a data resource for future analysis projects within a mitochondrial population genetics context.
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