Call-sSV Pipeline

• Overview
• How To Run
• Flow Diagram
• Pipeline Steps
• Inputs
• Outputs
• Testing and Validation
  • Test Data Set
  • Performance Validation
  • Validation Tool
• References
• License

Overview:

The call-sSV pipeline calls somatic structural variants utilizing DELLY and Manta. This pipeline requires at least one tumor sample and a matched normal sample. This pipeline is developed using Nextflow, docker and can run either on a single node linux machine or a multi-node HPC Slurm cluster.

How to Run:

Requirements

Currently supported Nextflow versions: v23.04.2

Run steps

Below is a summary of how to run the pipeline. See here for full instructions.

Pipelines should be run WITH A SINGLE SAMPLE AT A TIME. Otherwise resource allocation and Nextflow errors could cause the pipeline to fail.

1. The recommended way of running the pipeline is to directly use the source code located here: /hot/software/pipeline/pipeline-call-sSV/Nextflow/release/, rather than cloning a copy of the pipeline.

   • The source code should never be modified when running our pipelines

2. Create a config file for input, output, and parameters. An example for a config file can be found here. See Nextflow Config File Parameters for the detailed description of each variable in the config file.

   • Do not directly modify the source template.config, but rather you should copy it from the pipeline release folder to your project-specific folder and modify it there

3. Create the input YAML using the template.See Input YAML for detailed description of each column.

   • Again, do not directly modify the source template input YAML file. Instead, copy it from the pipeline release folder to your project-specific folder and modify it there.

4. The pipeline can be executed locally using the command below:

• YAML input

  nextflow run path/to/main.nf -config path/to/sample-specific.config -params-file path/to/input.yaml

• For example, path/to/main.nf could be: /hot/software/pipeline/pipeline-call-sSV/Nextflow/release/6.0.0-rc.1/main.nf

• path/to/sample-specific.config is the path to where you saved your project-specific copy of template.config

• path/to/input.yaml is the path to where you saved your sample-specific copy of input-sSV.yaml

To submit to UCLAHS-CDS's Azure cloud, use the submission script here with the command below:

python path/to/submit_nextflow_pipeline.py \
    --nextflow_script path/to/main.nf \
    --nextflow_config path/to/sample-specific.config \
    --nextflow_yaml path/to/input.yaml \
    --pipeline_run_name <sample_name> \
    --partition_type F16 \
    --email <your UCLA email, jdoe@ucla.edu>

In the above command, the partition type can be changed based on the size of the dataset. At this point, node F16 is generally recommended for larger datasets like A-full and node F2 for smaller datasets like A-mini.

* Manta SV calling wouldn't work on an F2 node due to incompatible resources. In order to test the pipeline for tasks not relevant to Manta, please set algorithm = ['delly'] in the sample specific config file.

Note: Because this pipeline uses an image stored in the GitHub Container Registry, you must follow the steps listed in the Docker Introduction on Confluence to set up a PAT for your GitHub account and log into the registry on the cluster before running this pipeline.

Flow Diagram:

Pipeline Steps:

Call Somatic Structural Variants - DELLY workflow:

1. Calling Single Sample Somatic Structural Variants

delly call --genome hg38.fa --exclude hg38.excl --map-qual 20 --min-clique-size 5 --mad-cutoff 15 --outfile t1.bcf tumor1.bam normal1.bam

This step requires an aligned and sorted tumor sample BAM file and a matched normal sample as an input for variant calling with DELLY. The stringent filters (--map-qual 20 --min-clique-size 5 --mad-cutoff 15) are added, which can drastically reduce the runtime, especially when the input BAMs are big. In the pipeline, these filters are specified in the NextFlow input parameters config file. If need be, these stringent filters can be adjusted in the config file.

2. Query the generated bcfs to get the sample names, which will be used in step 3.

echo -e "tumor\ncontrol" > samples_type
bcftools query -l t1.bcf > samples_name
paste samples_name samples_type > samples.tsv

3. Somatic Filtering

delly filter -f somatic -o t1.pre.bcf -s samples.tsv t1.bcf

This step applies somatic filtering against the .bcf file generated in Step 1.

Note: cohort based false positive filtering is compuationally heavy and not implemented in this pipeline.

Call Somatic Structural Variants - Manta workflow:

1. Calling Single Sample Somatic Structural Variants

configManta.py --normalBam "${normal_bam}" --tumorBam "${tumor_bam}" --referenceFasta "${reference_fasta}" --runDir MantaWorkflow
MantaWorkflow/runWorkflow.py

This step requires an aligned and sorted tumor sample BAM file and a matched normal sample as an input for variant calling with Manta.

Inputs

Input YAML

---
sample_id: "sample_id"
input:
  BAM:
    normal:
      - "/path/to/BAM"
    tumor:
      - "/path/to/BAM"

Nextflow Config File Parameters

An example of the NextFlow Input Parameters Config file can be found here.

Outputs

Testing and Validation

Test Data Set

Performance Validation

Testing was performed primarily in the Boutros Lab SLURM Development cluster. Metrics below will be updated where relevant with additional testing and tuning outputs.

References

• DELLY Structural Variant Caller
• Manta Structural Variant Caller

License

Authors: Yu Pan (YuPan@mednet.ucla.edu), Ghouse Mohammed (GMohammed@mednet.ucla.edu), Mohammed Faizal Eeman Mootor (MMootor@mednet.ucla.edu)

call-sSV is licensed under the GNU General Public License version 2. See the file LICENSE for the terms of the GNU GPL license.

call-sSV takes BAM files and utilizes DELLY and Manta to call somatic structural variants.

Copyright (C) 2021-2024 University of California Los Angeles ("Boutros Lab") All rights reserved.

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.