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Computational Analysis Tool for Comprehensive in vivo Transcription Factor Binding Studies in ChIP-exo and ChIP-Nexus Experiments

Show simple item record 2016-06-15T10:24:40Z 2016-06-15T10:24:40Z 2016-06-15
dc.title Computational Analysis Tool for Comprehensive in vivo Transcription Factor Binding Studies in ChIP-exo and ChIP-Nexus Experiments en
ethesis.discipline Genome-scale biology en
ethesis.faculty Medicinska fakulteten sv
ethesis.faculty Lääketieteellinen tiedekunta fi
ethesis.faculty Faculty of Medicine en
ethesis.faculty.URI Helsingfors universitet sv University of Helsinki en Helsingin yliopisto fi
dct.creator Hartonen, Tuomo Samuli
dct.issued 2016
dct.language.ISO639-2 eng
dct.abstract Novel experimental methods ChIP-exo and ChIP-Nexus allow studying transcription factor binding accurately in vivo. Only fraction of transcription factor binding mechanisms are yet fully understood and can be explained with simple positional weight matrix (PWM) models. Accurate knowledge of binding locations and patterns of transcription factors is key to understanding binding not explained by the current models. ChIP-exo and ChIP-Nexus experiments can also offer insights on the effects of single nucleotide polymorphism (SNP) at transcription factor binding sites on expression of the target genes. This is an important mechanism of action for disease-causing SNPs at non-coding genomic regions. In this thesis I describe a transcription factor binding site discovery software PeakXus specifically designed to leverage the increased resolution of ChIP-exo and ChIP-Nexus experiments. The key development principle of PeakXus is to make minimal number of assumptions of the data to allow discovery of novel binding patterns and mechanisms. PeakXus is tested with ChIP-Nexus and ChIP-exo experiments performed both in Homo sapiens and Drosophila melanogaster cell lines. PeakXus is shown to consistently find more peaks overlapping with a transcription factor-specific recognition sequence than published methods. As an application example I demonstrate how PeakXus can be coupled with Unique Molecular Identifiers (UMI) to measure the effect of a SNP overlapping with a transcription factor binding site on the in vivo transcription factor binding. The allele specific binding pipeline presented in this thesis takes better into account the read duplication bias and the varying coverage of the sequencing experiments than previous methods. en
dct.language en
ethesis.language English en
ethesis.language englanti fi
ethesis.language engelska sv
ethesis.supervisor Kivioja, Teemu
ethesis.thesistype pro gradu-avhandlingar sv
ethesis.thesistype pro gradu -tutkielmat fi
ethesis.thesistype master's thesis en
dct.identifier.ethesis E-thesisID:b4c41fbe-47f0-4ac1-8a4b-414e81dbd425
ethesis.degreeprogram Translationaalisen lääketieteen maisteriohjelma fi
ethesis.degreeprogram Master's Degree Programme in Translational Medicine en
ethesis.degreeprogram Magisterprogram i translationell medicin sv
ethesis-internal.timestamp.reviewStep 2016-06-07 12:26:35:580
dct.identifier.urn URN:NBN:fi:hulib-201606152422
dc.type.dcmitype Text Genome-scale biology en

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