search query: @instructor Hautaniemi, Sampsa / total: 5
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Author: | Alkodsi, Amjad |
Title: | Comparison of somatic copy number alteration detection algorithms in whole-genome and whole-exome data |
Publication type: | Master's thesis |
Publication year: | 2013 |
Pages: | 56 Language: eng |
Department/School: | Perustieteiden korkeakoulu |
Main subject: | Informaatiotekniikka (T-61) |
Supervisor: | Rousu, Juho ; Lundeberg, Joakim |
Instructor: | Hautaniemi, Sampsa ; Louhimo, Riku |
OEVS: | Electronic archive copy is available via Aalto Thesis Database.
Instructions Reading digital theses in the closed network of the Aalto University Harald Herlin Learning CentreIn the closed network of Learning Centre you can read digital and digitized theses not available in the open network. The Learning Centre contact details and opening hours: https://learningcentre.aalto.fi/en/harald-herlin-learning-centre/ You can read theses on the Learning Centre customer computers, which are available on all floors.
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Location: | P1 Ark Aalto | Archive |
Keywords: | somatic copy number alteration exome sequencing whole-genome sequencing SNP arrays |
Abstract (eng): | Somatic copy number alterations (SCNAs) constitute an important type of structural variations that affect cancer pathogenesis. Accurate detection of SCNAs is a crucial task as it can lead to identification of events driving cancer development. The advent of next-generation sequencing technologies has revolutionized the field of genomics and variant analysis. While whole-genome sequencing can give a broader view of the genome, whole-exome sequencing has the advantage of time and cost efficiency. Several algorithms have been developed to detect SCNAs from whole-genome and whole-exome sequencing data. However, their relative performance was not well described. In this thesis, we present a comparative analysis of six SCNA detection algorithms in sequencing data including ControlFreeC, BICseq, HMMcopy, CNAnorm, ExomeCNV and VarScan2. We use simulated data as well as a real dataset of 11 breast cancer samples subjected to whole-genome, whole-exome sequencing and SNP array genotyping. We address the relative strengths and limitations of each algorithm, and we explore the relative merits of using whole-genome over whole-exome sequencing data. |
ED: | 2013-09-25 |
INSSI record number: 47247
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