Identifikacija RNA izoformi iz grafa transkripata

master's thesis

• Title (english): Splice Isoform Identification from Transcript Graphs
• Author: Dario Pavlović
• Mentor: Mile Šikić (mentor)
• Committee member: Mile Šikić (predsjednik povjerenstva)
• Committee member: Damir Seršić (član povjerenstva)
• Committee member: Mladen Vučić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2015-07-03, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Mjerenje relativnih količina RNA transkripata u uzorku može biti vrlo važno za
različite primjene u biologiji i medicini. Sekvenciranje sljedeće generacije postaje
primarno korištena tehnologija za omogućavanje takvih analiza pružanjem osnovnih
podataka o uzorku. U ovome radu, prezentirao sam statistički model procjene količine
RNA koji koristi očitanja sekvenciranja sljedeće generacije s ciljem pronalaženja optimalnih vrijednosti relativnih količina. isomorph, programska implementacija ovog modela je opisana u radu. isomorph pokušava pronaći maksimum funkcije izglednosti po parametrima koji
predstavljaju relativne nivoe prisutnosti transkripata u uzorku. Testiranje je pokazalo
da za očitanja bez parova, isomorph ima zadovoljavajuću točnost, dok za očitanja u
parovima pokazuje potrebu za dodatnim poboljšanjima performansi. Dostupan je na
https://github.com/darxsys/isomorph.

Abstract (english)

Providing a measure of abundances of different RNA transcripts in a sample can
be very important in many different biological or medical studies. Next-generation
sequencing is becoming a technology of choice for providing fundamental data for
such analyses. In this work, I have presented an RNA abundance estimation model
that uses next-generation RNA-Seq reads to estimate optimal relative transcript abun-
dance values. isomorph, a software implementation of this method is presented
and explained. isomorph tries to maximize a likelihood function with regards to
isoform abundance levels to provide an optimal estimate of relative transcript abun-
dances in a sample. Testing has shown that for single-end reads, isomorph performs
well, while paired-end data performance should be more improved. It is available at
https://github.com/darxsys/isomorph.

• Keywords: rna-sekvenciranje; procjena količine; em algoritam
• Keywords (english): rna-seq; abundance estimation; em algorithm
• Language: english
• URN:NBN: urn:nbn:hr:168:950171
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2018-02-06 11:07:03