Detection and validation of genomic structural variation from DNA sequencing data

Placeholder Show Content


The comparison of individual genome sequences is a key task for modern studies of population genetics, genotype-phenotype associations, and genome evolution. The problem is difficult in part because commonly-used DNA sequencing hardware produces reads that are orders of magnitude smaller than the size of a single human chromosome. The detection of large genomic mutations known as structural variants (SVs) from these short sequencing reads has emerged has a particularly challenging problem. Numerous methods targeting this problem have been proposed, but it is difficult to assess their performance on real data since the ground truth is typically unknown. Moreover, complex SVs that escape detection by conventional algorithms are known to exist. We propose here a solution to both the complex SV detection problem and the issue of evaluating accuracy on real data.


Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2018; ©2018
Publication date 2018; 2018
Issuance monographic
Language English


Author Arthur, Joseph G
Degree supervisor Wong, Wing Hung
Thesis advisor Wong, Wing Hung
Thesis advisor Palacios Roman, Julia Adela
Thesis advisor Sabatti, Chiara
Degree committee member Palacios Roman, Julia Adela
Degree committee member Sabatti, Chiara
Associated with Stanford University, Department of Statistics.


Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Joseph G. Arthur.
Note Submitted to the Department of Statistics.
Thesis Thesis Ph.D. Stanford University 2018.
Location electronic resource

Access conditions

© 2018 by Joseph Glenn Arthur
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

Also listed in

Loading usage metrics...