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Introduction to Structural variant detection analyses

This course offers an introduction to SNP and SV detection data analysis by using advantages of short and long sequencing technologies.


Linux and knowledge of NGS formats Patience and perseverance


  • Handling mapping tools suitable for ILLUMINA and ONT data (bwa, minimap2)
  • SNP detection from mapping of short reads against a reference genome: SNP calling, filters and SNP annotation. Examples of possible studies based on SNP arrays
  • Detecting Structural Variations (SV) in short and long reads (breakdancer, sniffle)
  • SV detection from genome assembly and comparison (minimap2, nucmer, assemblytics, siry)

Learning objectives

  • Understanding limits and advantages of sequencing technology for SV detection
  • Manipulating short and long reads data on a virtual machine on jupyter environment
  • Handling mapping, SNP calling and SV detection tools and be able to analyse your own data
  • Detecting structural variations comparing assemblies.

Training material


  • Christine Tranchant (CT) -
  • Francois Sabot (FS) -
  • Julie Orjuela (JO) -
  • Alexis Dereeper (AD) -


Date Location Topics Participants Instructors Links Units
2022 Ouagadougour, Burkina Faso Introduction to SV detecton analyses 12 CT, JO, AD   UMR DIADE, PHIM
2022 Montpellier, France Introduction to SV detecton analyses 15 CT, FS, JO, AD   UMR DIADE, PHIM