Rapid Automated Large Structural Variation Detection in a Diploid Genome by NanoChannel Based Next-Generation Mapping
bioRxiv (Cold Spring Harbor Laboratory)2017
Citations Over Time
Alex Hastie, Ernest T. Lam, Andy Wing Chun Pang, Xinyue Zhang, Warren Andrews, Joyce Lee, Tiffany Y Liang, Jian Wang, Xiang Zhou, Zhanyang Zhu, Thomas Anantharaman, Željko Džakula, Sven Bocklandt, Urvashi Surti, Michael Saghbini, Michael D. Austin, Mark Borodkin, R. Erik Holmlin, Han Cao
Abstract
The human genome is diploid with one haploid genome inherited from the maternal and one from the paternal lineage. Within each haploid genome, large structural variants such as deletions, duplications, inversions, and translocations are extensively present and many are known to affect biological functions and cause disease. The ultimate goal is to resolve these large complex structural variants (SVs) and place them in the correct haploid genome with correct location, orientation, and copy number. Current methods such as karyotyping, chromosomal microarray (CMA), PCR-based tests, and nextgeneration sequencing fail to reach this goal either due to limited resolution, low throughput, or short read length.
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