Statistical and computational approaches for the analysis of high-throughput epigenomic data /

Epigenetic mechanisms, such as DNA modifications, are of great importance in all living things. Despite the importance of DNA modifications, many of the difficulties involved in establishing and characterizing epigenetic profiles discourage researchers from following this path of research. TOP-seq is the first DNA sequencing method which uses covalent labeling of unmodified individual CG sites, following by the synthesis of DNA polymerase. This DNA sequencing method combines the enrichment of the unmodified DNA fraction, the resolution of a single base, and the strand specificity. Several other TOP-seq-based sequencing methods that can identify other DNA modifications are currently being developed. However, to make full use of these methods, a set of appropriate statistical and computational methods is required. This study presents strategies to solve obstacles that arises from a very specific type of TOP-seq data. This study is based on three main parts: design, development, application. During the design part, we present a data processing strategy that converts primary TOP-seq epigenomic data into a CG position coverage signal. In the development section, we propose and integrate three signal transformations that enhance the signaling of enrichment-based epigenomic methods. Finally, we present several cases where the TOP-seq signal can be used to obtain biological information.

Grantor dc:publisher

Institutional Repository of Vilnius University

Year dc:date

2022

Author dc:creator

• Gibas, Povilas,

• epigenetics ; epigenomics ; DNA modification ; sequencing ; bioinformatics

Statement dc:rights

• info:eu-repo/semantics/openAccess

Language dc:language

eng

Repository record dc:identifier

https://repository.vu.lt/VU:ELABAETD130402765&prefLang=en_US

OAI identifier oai:identifier

oai:vu.lt:elaba:130402765