Bilkent University
Department of Computer Engineering


Whole Genome Inversion Detection


Marzieh E. Rasekh
MSc Student
Computer Engineering Department
Bilkent University

With advances in whole genome sequencing techniques , studies have revealed the role of structural variations (SVs) in human phenotype, genetic diseases, and disease susceptibility. It has been observed that structural variations can comprise millions of nucleotides in every genome. In the last few years significant efforts have been made to map and characterize SVs in the human genome, however our understanding of inversions variant lags behind. While unbalanced SVs such as deletions and duplications resulting in unbalanced variant can be easily detected by array-based approaches, inversions which cause variation in the orientation of the genome, cannot be observed by such methods. Many computational methods based on mapping single-end and paired-end reads to the reference genome and searching for specific patterns have been proposed to detect large-scale inversions. Few investigated inversions have been reported in literature but the number is very limited. The complexity of such regions and the large size of data remains a major challenge. Here we propose a combinatorial optimization algorithm to detect structural variations from various formats of reads. Our aim is to offer a method that will be adaptable and scalable for different sequencing technologies.


DATE: 28 April, 2014, Monday @ 17:10