Neusomatic

Introduction

NeuSomatic is based on deep convolutional neural networks for accurate somatic mutation detection. With properly trained models, it can robustly perform across sequencing platforms, strategies, and conditions. NeuSomatic summarizes and augments sequence alignments in a novel way and incorporates multi-dimensional features to capture variant signals effectively. It is not only a universal but also accurate somatic mutation detection method.

For more information, please check:
Docker hub: https://hub.docker.com/r/msahraeian/neusomatic/
Home page: https://github.com/bioinform/neusomatic

Versions

  • 0.2.1

Commands

  • call.py

  • dataloader.py

  • extract_postprocess_targets.py

  • filter_candidates.py

  • generate_dataset.py

  • long_read_indelrealign.py

  • merge_post_vcfs.py

  • merge_tsvs.py

  • network.py

  • postprocess.py

  • preprocess.py

  • resolve_scores.py

  • resolve_variants.py

  • scan_alignments.py

  • split_bed.py

  • train.py

  • utils.py

Module

You can load the modules by:

module load biocontainers
module load neusomatic

Example job

Warning

Using #!/bin/sh -l as shebang in the slurm job script will cause the failure of some biocontainer modules. Please use #!/bin/bash instead.

To run neusomatic on our clusters:

#!/bin/bash
#SBATCH -A myallocation     # Allocation name
#SBATCH -t 1:00:00
#SBATCH -N 1
#SBATCH -n 1
#SBATCH --job-name=neusomatic
#SBATCH --mail-type=FAIL,BEGIN,END
#SBATCH --error=%x-%J-%u.err
#SBATCH --output=%x-%J-%u.out

module --force purge
ml biocontainers neusomatic