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, NikoThesis advisor
Mohammadi, PejmanKeywords
statistical modeling, PAR-CLIP, RNA-binding proteins, Bayesian analysis