SVCurator: A Crowdsourcing app to visualize evidence of structural variants for the human genome

Research output: Other contributionMiscellaneous

Abstract

A high quality benchmark for small variants encompassing 88 to 90% of the reference genome has been developed for seven Genome in a Bottle (GIAB) reference samples. However a reliable benchmark for large indels and structural variants (SVs) is yet to be defined. In this study, we manually curated 1235 SVs which can ultimately be used to evaluate SV callers or
train machine learning models. We developed a crowdsourcing app - SVCurator - to help curators manually review large indels and SVs within the human genome, and report their genotype and size accuracy.

SVCurator is a Python Flask-based web platform that displays images from short, long, and linked read sequencing data from the GIAB Ashkenazi Jewish Trio son [NIST RM 8391/HG002]. We asked curators to assign labels describing SV type (deletion or insertion), size accuracy, and genotype for 1235 putative insertions and deletions sampled from different size bins between 20 and 892,149 bp. The crowdsourced results were highly concordant with 37 out of
the 61 curators having at least 78% concordance with a set of ‘expert’ curators, where there was 93% concordance amongst ‘expert’ curators. This produced high confidence labels for 935 events. When compared to the heuristic-based draft benchmark SV callset from GIAB, the SVCurator crowdsourced labels were 94.5% concordant with the benchmark set. We found that curators can successfully evaluate putative SVs when given evidence from multiple sequencing technologies.

Details

Authors
  • Lesley M Chapman
  • Noah Spies
  • Patrick Pai
  • Chun Shen Lim
  • Andrew Carroll
  • Giuseppe Narzisi
  • Christopher M Watson
  • Christos Proukakis
  • Wayne E Clarke
  • Naoki Nariai
  • Eric Dawson
  • Garan Jones
  • Daniel Blankenberg
  • Chunlin Xiao
  • Sree Rohit Raj Kolora
  • Noah Alexander
  • Paul Wolujewicz
  • Azza Ahmad
  • Graeme Smith
  • Saadlee Shehreen
  • Aaron M Wenger
  • Marc Salit
  • Justin M Zook
Organisations
External organisations
  • National Institute of Standards and Technology (NIST)
  • University of Maryland
  • University of Otago
  • St James's University Hospital
  • University College London
  • National Cancer Institute, NCI
  • National Institutes of Health, United States
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Bioinformatics (Computational Biology)
  • Bioinformatics and Systems Biology
  • Medical Genetics

Keywords

  • Bioinformatics, Genomics, Structural variants, Benchmark datasets
Original languageEnglish
PublisherbioRxiv
Number of pages35
Publication statusPublished - 2019 Mar 26
Publication categoryResearch