@article {539, title = {SVachra: a tool to identify genomic structural variation in mate pair sequencing data containing inward and outward facing reads.}, journal = {BMC Genomics}, volume = {18}, year = {2017}, month = {2017 Oct 03}, pages = {691}, abstract = {

BACKGROUND: Characterization of genomic structural variation (SV) is essential to expanding the research and clinical applications of genome sequencing. Reliance upon short DNA fragment paired end sequencing has yielded a wealth of single nucleotide variants and internal sequencing read insertions-deletions, at the cost of limited SV detection. Multi-kilobase DNA fragment mate pair sequencing has supplemented the void in SV detection, but introduced new analytic challenges requiring SV detection tools specifically designed for mate pair sequencing data. Here, we introduce SVachra - Structural Variation Assessment of CHRomosomal Aberrations, a breakpoint calling program that identifies large insertions-deletions, inversions, inter- and intra-chromosomal translocations utilizing both inward and outward facing read types generated by mate pair sequencing.

RESULTS: We demonstrate SVachra{\textquoteright}s utility by executing the program on large-insert (Illumina Nextera) mate pair sequencing data from the personal genome of a single subject (HS1011). An additional data set of long-read (Pacific BioSciences RSII) was also generated to validate SV calls from SVachra and other comparison SV calling programs. SVachra exhibited the highest validation rate and reported the widest distribution of SV types and size ranges when compared to other SV callers.

CONCLUSIONS: SVachra is a highly specific breakpoint calling program that exhibits a more unbiased SV detection methodology than other callers.

}, keywords = {Genetic Variation, Genomics, Sequence Analysis, DNA}, issn = {1471-2164}, doi = {10.1186/s12864-017-4021-y}, author = {Hampton, Oliver A and English, Adam C and Wang, Mark and Salerno, William J and Liu, Yue and Muzny, Donna M and Han, Yi and Wheeler, David A and Worley, Kim C and Lupski, James R and Gibbs, Richard A} } @article {177, title = {Assessing structural variation in a personal genome-towards a human reference diploid genome.}, journal = {BMC Genomics}, volume = {16}, year = {2015}, month = {2015 Apr 11}, pages = {286}, abstract = {

BACKGROUND: Characterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods.

RESULTS: We demonstrate Parliament{\textquoteright}s efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8\%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus.

CONCLUSIONS: HS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.

}, keywords = {Computational Biology, Databases, Genetic, Diploidy, Genome, Human, Genomic Structural Variation, Humans, Sequence Analysis, DNA, Software}, issn = {1471-2164}, doi = {10.1186/s12864-015-1479-3}, author = {English, Adam C and Salerno, William J and Hampton, Oliver A and Gonzaga-Jauregui, Claudia and Ambreth, Shruthi and Ritter, Deborah I and Beck, Christine R and Davis, Caleb F and Dahdouli, Mahmoud and Ma, Singer and Carroll, Andrew and Veeraraghavan, Narayanan and Bruestle, Jeremy and Drees, Becky and Hastie, Alex and Lam, Ernest T and White, Simon and Mishra, Pamela and Wang, Min and Han, Yi and Zhang, Feng and Stankiewicz, Pawel and Wheeler, David A and Reid, Jeffrey G and Muzny, Donna M and Rogers, Jeffrey and Sabo, Aniko and Worley, Kim C and Lupski, James R and Boerwinkle, Eric and Gibbs, Richard A} }