Comparison of Somatic copy number alteration detection algorithms in whole-genome and whole-exome data
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Somatic copy number alterations (SCNAs) are an important type of structural variations that affect cancer pathogenesis. Accirate 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 and efficiency 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 strenths and limitations of each algorith, and we explore the relative merits of using whole-genome over whole-exome sequencing data.
Place, publisher, year, edition, pages
Engineering and Technology
IdentifiersURN: urn:nbn:se:kth:diva-173886OAI: oai:DiVA.org:kth-173886DiVA: diva2:855720