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SaVor - A Reproducible Structural Variant Calling and Benchmarking Platform from Short-Read Data.

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  • 1Department of Biology, San Diego State University.

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Summary
This summary is machine-generated.

SaVor is a new workflow for identifying structural variations (SVs) in genomes using short-read sequencing data. It offers flexibility and reproducibility, aiding in the analysis of genomic differences.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Structural variations (SVs) are genomic differences >1 kilobase-pair (Kbp) arising from DNA repair, genome duplication, or transposable elements.
  • Next-generation sequencing (NGS) has increased short-read genomic data, necessitating efficient SV detection methods.

Purpose of the Study:

  • To introduce SaVor, a flexible and reproducible workflow for structural variation (SV) calling.
  • To generate a consensus SV call-set from short-read sequencing data using user-defined merge parameters.

Main Methods:

  • SaVor accepts single or multi-lane short-read paired-end Illumina data or BAM files.
  • The workflow was tested on 1,165 *Arabidopsis thaliana* whole genome sequences.
  • Performance was benchmarked against SVs identified using Lumpy.

Main Results:

  • Intersection calls (SVs supported by 3 callers) achieved high precision (>0.91) but lower recall (<0.51).
  • Union calls (SVs supported by at least 1 caller) showed high recall (>0.88) but lower precision (<0.57).
  • Merge strategies impact the trade-off between precision and recall for SV call-sets.

Conclusions:

  • SaVor provides a reproducible method for SV calling from short-read data.
  • Downstream analysis requires careful consideration of precision-recall trade-offs based on the chosen merge strategy.
  • SaVor is an open-source Snakemake pipeline available on GitHub.