Quick reference

• The official lumpy-sv container image.

• Maintained by: openEuler CloudNative SIG.

• Where to get help: openEuler CloudNative SIG, openEuler.

lumpy-sv | openEuler

Current lumpy-sv docker images are built on the openEuler. This repository is free to use and exempted from per-user rate limits.

lumpy-sv is a general probabilistic framework for structural variant discovery.

Learn more on lumpy-sv website.

Supported tags and respective Dockerfile links

The tag of each lumpy-sv container image is consist of the version of lumpy-sv and the version of basic image. The details are as follows

Tags	Currently	Architectures
0.3.1-oe2403sp1	lumpy-sv 0.3.1 on openEuler 24.03-LTS-SP1	amd64, arm64

Usage

• Pull the openeuler/lumpy-sv image from hub.docker.com

  docker pull openeuler/lumpy-sv:{Tag}
  

• Start a lumpy-sv instance

  docker run -it --name my-lumpy-sv openeuler/lumpy-sv:{Tag}
  

  Now, you can use lumpy by your requirements.

  Flexible and customizable breakpoint detection for advanced users.

  usage:    lumpy [options]
  

  Options

      -g       Genome file (defines chromosome order)
      -e       Show evidence for each call
      -w       File read windows size (default 1000000)
      -mw      minimum weight across all samples for a call
      -msw     minimum per-sample weight for a call
      -tt      trim threshold
      -x       exclude file bed file
      -t       temp file prefix, must be to a writeable directory
      -P       output probability curve for each variant
      -b       output as BEDPE instead of VCF
  
      -sr      bam_file:<file name>,
              id:<sample name>,
              back_distance:<distance>,
              min_mapping_threshold:<mapping quality>,
              weight:<sample weight>,
              min_clip:<minimum clip length>,
              read_group:<string>
  
      -pe      bam_file:<file name>,
              id:<sample name>,
              histo_file:<file name>,
              mean:<value>,
              stdev:<value>,
              read_length:<length>,
              min_non_overlap:<length>,
              discordant_z:<z value>,
              back_distance:<distance>,
              min_mapping_threshold:<mapping quality>,
              weight:<sample weight>,
              read_group:<string>
  
      -bedpe   bedpe_file:<bedpe file>,
              id:<sample name>,
              weight:<sample weight>
  

Question and answering

If you have any questions or want to use some special features, please submit an issue or a pull request on openeuler-docker-images.