en
Master
English

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

ContributorsAkarsu, Hatice
Master program titleMaster of Bioinformatics and Biological Data Analysis (BIADB)
Defense date2013
Abstract

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.

eng
Keywords
  • DNase-seq
  • Automated analysis
  • Footprints
  • DNase Hypersensitive Sites (DHS)
  • Hidden Markov Model
Citation (ISO format)
AKARSU, Hatice. DNase-I sequencing data: development of an analysis pipeline with a Hidden Markov Model approach. 2013.
Main files (1)
Master thesis
accessLevelRestricted
Identifiers
  • PID : unige:34410
289views
7downloads

Technical informations

Creation02/19/2014 10:00:00 PM
First validation02/19/2014 10:00:00 PM
Update time03/14/2023 8:59:13 PM
Status update03/14/2023 8:59:13 PM
Last indexation01/29/2024 8:05:12 PM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack