Andrew Carroll, Director of Science at DNAnexus, presents how to greatly improve the accuracy of SV-calling by using long-read PacBio sequencing and fast and easy-to-run cloud-optimized apps like PBHoney, Parliament, and Sniffles.
Fritz Sedlazeck, a postdoc at Johns Hopkins University, describes his structural variant detection tool Sniffles in this poster from AGBT 2016. Included: examples of structural variants that could not be detected with other algorithms.
Structural Variants (SVs), which include deletions, insertions, duplications, inversions and chromosomal rearrangements, have been shown to effect organism phenotypes, including changing gene expression, increasing disease risk, and playing an important role in cancer development. Still it remains challenging to detect all types of SVs from high throughput sequencing data and it is even harder to detect more complex SVs such as a duplication nested within an inversion. To overcome these challenges we developed algorithms for SV analysis using longer third generation sequencing reads. The increased read lengths allow us to span more complex SVs and accurately assess SVs in repetitive…
Structural variant calling combining Illumina and low-coverage Pacbio Detection of large genomic variation (structural variants) has proven challenging using short-read methods. Long-read approaches which can span these large events have promise to dramatically expand the ability to accurately call structural variants. Although sequencing with Pacific Biosciences (Pacbio) long-read technology has become increasingly high throughput, generating high coverage with the technology can still be limiting and investigators often would like to know what pacbio coverages are adequate to call structural variants. Here, we present a method to identify a substantially higher fraction of structural variants in the human genome using low-coverage…