Understanding The Complexity of Human Structural Genomic Variation Through Multiple Whole Genome Sequencing Platforms

genomic structural variants;computational pipeline;Genetics;Health Sciences;Bioinformatics

Zhao, XuefangLi, Jun ;

University of Michigan

关键词: genomic structural variants;    computational pipeline;    Genetics;    Health Sciences;    Bioinformatics;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/138462/xuefzhao_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Genomic structural variants (SVs) are major sources of genome diversity and closely related to human health, as indicated by numerous studies. In spite of the recent advances in sequencing technology and discovery methodology, there are still considerable amounts of variants in the genome that are partially or completely misinterpreted. This thesis has mainly focused on comprehensively interpreting the structural variants in human genomes by accurately defining the locations and formats of variants with the application of different sequencing platforms. To accomplish this goal, I developed a randomized iterative approach to define all types of SVs, which has shown superior performance in accurately defining complex variants. Next, I built a recurrence based validation pipeline to systematically validate SVs with long read sequences. I conclude with a systematic integration of SVs in multiple individuals discovered by various short read based detecting algorithms, with supportive evidence from orthogonal technologies, which presents to date the most comprehensive SV map in the human genome and the best current technologies allow us to do.