Skip to main content
ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #303546

Title: Using the whole read: structural variant detection using NGS data

item Bickhart, Derek
item Cole, John
item Hutchison, Jana
item XU, LINGYANG - University Of Maryland
item Liu, Ge - George

Submitted to: World Congress of Genetics Applied in Livestock Production
Publication Type: Proceedings
Publication Acceptance Date: 4/21/2014
Publication Date: 8/17/2014
Citation: Bickhart, D.M., Cole, J.B., Hutchison, J.L., Xu, L., Liu, G. 2014. Using the whole read: structural variant detection using NGS data. World Congress of Genetics Applied in Livestock Production. Vancouver, Canada, Aug. 17–22. 5 pp.

Interpretive Summary:

Technical Abstract: Several classes of Structural Variants (SV) remain difficult to detect within sequenced genomes. Deletions and tandem duplications may affect a large proportion of variable genomic sequence space, yet their detection is still difficult to discern from false positive signals. Here, we present a method for detecting such variants from short-read sequence data using the orientation and distance of paired-end, and split-read mappings in addition to using read-depth as a filtering agent. We test our data using simulated SVs and find that our method is 27.5 times more precise than a competing detection program in detecting tandem duplications. Our method is also able to detect three times the number of deletions than the competition. This high degree of precision should enable better functional prediction of SVs from short-read sequence data.