A snakemake pipeline to call structural variants from tumor-only ONT data

⚠️ This pipeline is in its early stages. Please use with caution.

Author

Minghao Jiang, [email protected]

Tools used

• SV callers

  cuteSV, Sniffles, SVIM, SVision, Severus, NanoSV, NanoVar, Delly, Debreak

• Annotation tools

  AnnotSV, VEP (release/111), SnpEff

• R packages

  vroom, tibble, glue, dplyr, tidyr, purrr, GenomicRanges, stringr, BiocParallel, parallel

• Other tools

  Minimap2, SAMtools, BCFtools, SURVIVOR, vcf2maf (1.6.21), SnpSift, duphold

Pipeline structure

%%{
  init: {
    'theme': 'base',
    'themeVariables': {
      'fontFamily': 'Comic Sans MS',
      'primaryColor': '#ACD98DFF',
      'primaryTextColor': 'black',
      'lineColor': 'black',
      'secondaryColor': 'grey',
      'tertiaryColor': '#EEEEEE'
    }
  }
}%%

flowchart TD

  classDef norm stroke-width: 1px, stroke: black;
  classDef tool fill: #FFB977FF, padding: 0px, margin: 0px, stroke-width: 1px, stroke: black;
  classDef other_file stroke-dasharray: 5 5, stroke-width: 1px, stroke: black;
  classDef other_tool fill: #FFB977FF, padding: 0px, margin: 0px, stroke-dasharray: 5 5, stroke-width: 1px, stroke: black;
  classDef output fill: #98D9E4FF, stroke-width: 1px, stroke: black;

  fastq@{ shape: lean-r, label: "FASTQ" }
  bam([BAM])
  cutesv_vcf([VCF])
  sniffles2_vcf([VCF])
  cutesv_filtered_vcf([filtered
  VCF])
  sniffles2_filtered_vcf([filtered
  VCF])
  merged_vcf([merged VCF])
  annotated_vcf([annotated VCF/TSV])
  somatic_vcf@{ shape: lean-l, label: "somatic SVs" }
  germline_vcf@{ shape: lean-l, label: "germline SVs" }
  other_vcfs([VCFs])
  other_filtered_vcf([filtered
  VCFs])
  minimap2@{ shape: tag-rect, label: "Minimap2" }
  cutesv@{ shape: tag-rect, label: "cuteSV"  }
  sniffles2@{ shape: tag-rect, label: " Sniffles2 " }
  other_callers@{ shape: tag-rect, label: "other\ncallers" }
  bcftools@{ shape: tag-rect, label: "BCFtools" }
  survivor@{ shape: tag-rect, label: "SURVIVOR" }
  anno_tools@{ shape: tag-rect, label: "VEP, AnnotSV, SnpEff" }

  fastq:::norm
  bam:::norm
  cutesv_vcf:::norm
  sniffles2_vcf:::norm
  other_vcfs:::other_file
  cutesv_filtered_vcf:::norm
  sniffles2_filtered_vcf:::norm
  other_filtered_vcf:::other_file
  merged_vcf:::norm
  annotated_vcf:::norm
  somatic_vcf:::output
  germline_vcf:::output

  minimap2:::tool
  cutesv:::tool
  sniffles2:::tool
  other_callers:::other_tool
  bcftools:::tool
  survivor:::tool
  anno_tools:::tool

  fastq --> minimap2 --> bam
  bam --> cutesv --> cutesv_vcf --> bcftools --> cutesv_filtered_vcf --> survivor
  bam --> sniffles2 --> sniffles2_vcf --> bcftools --> sniffles2_filtered_vcf --> survivor
  bam -.-> other_callers -.-> other_vcfs -.-> bcftools -.-> other_filtered_vcf -.-> survivor
  survivor --> merged_vcf --> anno_tools --> annotated_vcf
  annotated_vcf --> somatic_vcf
  annotated_vcf --> germline_vcf

Loading

Getting started

Prerequisites

1. Clone this repo and navigate into it:

   git clone https://github.com/jasonwong-lab/smk_sv.git
   cd smk_sv

   • Follow all steps below after you are in the top dir of this repo.
   • Uncomment all rules in the Snakefile.
   • Check the predefined wildcards_constraints in the Snakefile and modify/delete it if necessary.
   • Using a JSON schema to validate the configuration file might prevent Snakemake from monitoring changes to the parameters. You can comment the validate(config, "config/config.schema.json") in the Snakefile.

2. Install AnnotSV manually.

   • AnnotSV is not included in the image due to its large annotation resources (~ 20GB) that cannot be specified elsewhere.
   • Creating a lock file for each combination of sample and type_sv has been implemented. However, AnnotSV might still encounter errors since it doesn’t support processing multiple files within the same directory. To address this, an additional resource parameter constraint_annotsv=1 has been added to the rule annotate_sv_annotsv to ensure that only one instance of AnnotSV runs at a time. You can modify this parameter in workflow/profile/default/config.yaml where its default is 1.

Configuration

1. Prepare config files:

   1. Copy config/config-test.yaml to config/config.yaml.
      • Adjust the configuration settings according to your project's needs.
      • Specification of important elements:
        • dir_run: working directory where all results will be stored.
        • mapper: dict whose keys are names of mappers and values (boolean) indicate whether perform mapping or not. Only the first mapper will be used. When a mapper is specified and its value is false, no mapping by this mapper will be performed, but its results will be used in the following steps.
        • callers: dict whose keys are names of callers and values (boolean) indicate whether perform SV calling using this caller or not. When a caller is specified and its value is false, no SV calling by this caller will be performed, but its results will be used in the following steps.
        • types_sv: SV types to be called. BND indicates translocations.
        • threads: number of CPUs of each rule to be used.
        • ...
   2. Copy workflow/profiles/default/config-test.yaml to workflow/profiles/default/config.yaml.
      • Bind directories you need in the container.
      • Change the number of CPUs you prefer.
      • Modify/add/delete other parameters of this snakemake pipeline.

2. Prepare sample data:

   1. Copy config/pep/samples-test.csv to config/pep/samples.csv, and update sample_name in the csv.
   2. Copy config/pep/config-test.yaml and config/pep/config.yaml. More information please see Portable Encapsulated Projects (PEP).

3. Set up Conda environments:

   snakemake --conda-create-envs-only

Execution

• Run the pipeline locally:

  snakemake

• Run the pipeline on a cluster: If you want to run this pipeline on a cluster (e.g., SLURM, or PBS), you should customise your own profile and place it into ~/.config/snakemake/, and then run the pipeline with the profile you have set as a parameter:

  snakemake --profile <your_profile_name>

  Or run the pipeline with the profile you have set as an environment variable:

  export SNAKEMAKE_PROFILE=<your_profile_name>
  snakemake

  You can refer to the profile I have been using at workflow/profiles/mycluster, or turn to snakemake websites.

Note for Cluster Users

If you are using a cluster that does not support Singularity well, please switch to the without_docker branch. This branch is tailored for environments where containers might not be the best option.

git checkout without_docker

License

Codes here are licensed under the GNU General Public License v3.