A comparative study of structural variant calling strategies using the Alzheimer′s Disease Sequencing Project′s whole genome family data

• Published in: bioRxiv
• Main Authors: Malamon, John S, Farrell, John J, Li Charlie Xia, Dombroski, Beth A, Wan-Ping, Lee, Das, Rueben G, Vardarajan, Badri N, Way, Jessica, Kuzma, Amanda B, Valladares, Otto, Leung, Yuk Yee, Scanlon, Allison, Barrera Lopez, Irving Antonio, Brehony, Jack, Worley, Kim C, Zhang, Nancy R, Li-San, Wang, Farrer, Lindsay A, Schellenberg, Gerard D
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 20.05.2022
• Subjects: Alzheimer's disease; Breakpoints; Computer applications; Genomes; Genotyping; Insertion; Nucleotide sequence; Parliaments; Quality control; Sensitivity analysis
• DOI: 10.1101/2022.05.19.492472

Background: Reliable detection and accurate genotyping of structural variants (SVs) and insertion/deletions (indels) from whole-genome sequence (WGS) data is a significant challenge. We present a protocol for variant calling, quality control, call merging, sensitivity analysis, in silico genotyping, and laboratory validation protocols for generating a high-quality deletion call set from whole genome sequences as part of the Alzheimer′s Disease Sequencing Project (ADSP). This dataset contains 578 individuals from 111 families. Methods: We applied two complementary pipelines (Scalpel and Parliament) for SV/indel calling, break-point refinement, genotyping, and local reassembly to produce a high-quality annotated call set. Sensitivity was measured in sample replicates (N=9) for all callers using in silico variant spike-in for a wide range of event sizes. We focused on deletions because these events were more reliably called. To evaluate caller specificity, we developed a novel metric called the D-score that leverages deletion sharing frequencies within and outside of families to rank recurring deletions. Assessment of overall quality across size bins was measured with the kinship coefficient. Individual callers were evaluated for computational cost, performance, sensitivity, and specificity. Quality of calls were evaluated by Sanger sequencing of predicted loss-of-function (LOF) variants, variants near AD candidate genes, and randomly selected genome-wide deletions ranging from 2 to 17,000 bp. Results: We generated a high-quality deletion call set across a wide range of event sizes consisting of 152,301 deletions with an average of 263 per genome. A total of 114 of 146 predicted deletions (78.1%) were validated by Sanger sequencing. Scalpel was more accurate in calling deletions ≤100 bp, whereas for Parliament, sensitivity was improved for deletions > 900 bp. We validated 83.0% (88/106) and 72.5% (37/51) of calls made by Scalpel and Parliament, respectively. Eleven deletions called by both Parliament and Scalpel in the 101-900 bin were tested and all were confirmed by Sanger sequencing. Conclusions: We developed a flexible protocol to assess the quality of deletion detection across a wide range of sizes. We also generated a truth set of Sanger sequencing validated deletions with precise breakpoints covering a wide spectrum of sizes between 1 and 17,000 bp. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://dss.niagads.org/datasets/ng00067/