DNase-I sequencing data: development of an analysis pipeline with a Hidden Markov Model approach

Diplôme Master DNase-I sequencing data: development of an analysis pipeline with a Hidden Markov Model approach eng 2013 author Akarsu Hatice 753177 director Rougemont Jacques 85451 DNase-sequencing is a high-throughput method that allows the genome-wide mapping of open active chromatin by using a DNase-I digestion and the in vivo identification of proteins DNA binding sites that have been protected from enzymatic digestion. This phenomena is called "footprinting". The goal of this master project is the set up of a pipeline for an automated DNase-sequence data analysis, starting with public human stem cells DNase-sequencing data from ENCODE (n=8). Our approach is based on two well known methods: a peak calling program to narrow down the data on the most relevant signal regions, followed by a footprints identification by using a 3-states Hidden Markov Model algorithm. Our preliminary pipeline, though being far from completion, shows already some promising results. DNase-seq Automated analysis Footprints DNase Hypersensitive Sites (DHS) Hidden Markov Model Dewey 570 Master of Bioinformatics and Biological Data Analysis (BIADB) 30 Section de biologie 16 false 360ba2d8-0312-4748-8b9a-5e60bfe2f37c Master thesis Restricted Akarsu_Master_Report_2013.pdf 6026874 application/pdf restrictedAccess Faculté des sciences / Section de biologie

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DNase-I sequencing data: development of an analysis pipeline with a Hidden Markov Model approach				2013	341	7

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Akarsu, Hatice