Statistical analysis of PAR-CLIP data

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School of Science | Master's thesis
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Date

2013

Department

Perustieteiden korkeakoulu

Major/Subject

Informaatiotekniikka

Mcode

T-61

Degree programme

Language

en

Pages

51

Series

Abstract

From creation to its degradation, the RNA molecule is the action field of many binding proteins with different roles in regulation and RNA metabolism. Since these proteins are involved in a large number of processes, a variety of diseases are related to abnormalities occurring within the binding mechanisms. One of the experimental methods for detecting the binding sites of these proteins is PAR-CLIP built on the next generation sequencing technology. Due to its size and intrinsic noise, PAR-CLIP data analysis requires appropriate pre-processing and thorough statistical analysis. The present work has two main goals. First, to develop a modular pipeline for pre-processing PAR-CLIP data and extracting necessary signals for further analysis. Second, to devise a novel statistical model in order to carry out inference about presence of protein binding sites based on the Signals extracted in the pre-processing step.

Description

Supervisor

Lähdesmäki, Harri|Aurell, Erik|Beerenwinkel, Niko

Thesis advisor

Mohammadi, Pejman

Keywords

statistical modeling, PAR-CLIP, RNA-binding proteins, Bayesian analysis

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