Pepper_deepvariant

Introduction

PEPPER is a genome inference module based on recurrent neural networks that enables long-read variant calling and nanopore assembly polishing in the PEPPER-Margin-DeepVariant pipeline.

Versions

• r0.8

• r0.8-gpu

Commands

• call_variants

• freeze_graph

• make_examples

• model_eval

• model_train

• multisample_make_examples

• pepper

• pepper_train

• pepper_variant

• pepper_variant_train

• postprocess_variants

• run_deepvariant

• run_deepvariant.py

• run_pepper_margin_deepvariant

• run-prereq.sh

• runtime_by_region_vis

• settings.sh

• show_examples

• vcf_stats_report

Example job

Adjust slurm options based on job requirements (slurm cheat sheet):

#!/bin/bash
#SBATCH -p partitionName  # batch, gpu, preempt, mpi or your group's own partition
#SBATCH -t 1:00:00  # Runtime limit (D-HH:MM:SS)
#SBATCH -N 1   # Number of nodes
#SBATCH -n 1   # Number of tasks per node
#SBATCH -c 4   # Number of CPU cores per task
#SBATCH --mem=8G       # Memory required per node
#SBATCH --job-name=pepper_deepvariant  # Job name
#SBATCH --mail-type=FAIL,BEGIN,END     # Send an email when job fails, begins, and finishes
#SBATCH --mail-user=your.email@tufts.edu       # Email address for notifications
#SBATCH --error=%x-%J-%u.err   # Standard error file: <job_name>-<job_id>-<username>.err
#SBATCH --output=%x-%J-%u.out  # Standard output file: <job_name>-<job_id>-<username>.out

module purge   ### Optional, but highly recommended.
module load pepper_deepvariant/XXXX    ### Latest version is recommended.