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variant_calling_docker_gpu_quickstart.md

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Variant calling quickstart (Using docker)

Here we show a quickstart for using GPU-enabled NVIDIA-docker in your system.

Install CUDA and NVIDIA-docker

Expand to see CUDA + NVIDIA-docker installation guide.
Preprocessing: Install CUDA [must be installed by root]

Install CUDA toolkit 11.0 from the CUDA archive.

Here are the instructions to install CUDA 11.0 on Ubuntu 20.04LTS:

# Verify you have CUDA capable GPUs:
lspci | grep -i nvidia

# Verify Linux version
uname -m && cat /etc/*release
# Expected output: x86_64

sudo apt-get -qq -y update
sudo apt-get -qq -y install gcc wget make

# Install proper kernel headers: This is for ubuntu
# Details: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html
sudo apt-get install linux-headers-$(uname -r)

wget https://developer.download.nvidia.com/compute/cuda/11.2.0/local_installers/cuda_11.2.0_460.27.04_linux.run
sudo sh cuda_11.2.0_460.27.04_linux.run
Step 1.1: Install docker

Please install docker and wget if you don't have it installed already. You can install docker for other distros from here:

We show the installation instructions for Ubuntu here:

# Install wget to download data files.
sudo apt-get -qq -y update
sudo apt-get -qq -y install wget

# Install docker using instructions on:
# https://docs.docker.com/install/linux/docker-ce/ubuntu/
sudo apt-get -qq -y install apt-transport-https ca-certificates curl gnupg-agent software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -

sudo add-apt-repository \
"deb [arch=amd64] https://download.docker.com/linux/ubuntu \
$(lsb_release -cs) \
stable"

sudo apt-get -qq -y update
sudo apt-get -qq -y install docker-ce
docker --version

# To add the user to avoid running docker with sudo:
# Details: https://docs.docker.com/engine/install/linux-postinstall/

sudo groupadd docker
sudo usermod -aG docker $USER

# Log out and log back in so that your group membership is re-evaluated.

# After logging back in.
docker run hello-world

# If you can run docker without sudo then change the following commands accordingly.
Step 1.1: Install nvidia-docker

Install nvidia docker following these instructions.

distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
&& curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \
&& curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

sudo apt-get update

sudo apt-get install -y nvidia-docker2

sudo systemctl restart docker

sudo docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi
# The output show show all your GPUs, if you enabled Docker for users then you should be able to run nvidia-docker without sudo

Quickstart: Nanopore variant calling

BASE="${HOME}/gpu-quickstart"

# Set up input data
INPUT_DIR="${BASE}/input/data"
REF="GRCh38_no_alt.chr20.fa"
BAM="HG002_ONT_2_GRCh38.chr20.quickstart.bam"

# Set the number of CPUs to use
THREADS="1"

# Set up output directory
OUTPUT_DIR="${BASE}/output"
OUTPUT_PREFIX="HG002_ONT_2_GRCh38_PEPPER_Margin_DeepVariant.chr20"
OUTPUT_VCF="HG002_ONT_2_GRCh38_PEPPER_Margin_DeepVariant.chr20.vcf.gz"
TRUTH_VCF="HG002_GRCh38_1_22_v4.2.1_benchmark.quickstart.vcf.gz"
TRUTH_BED="HG002_GRCh38_1_22_v4.2.1_benchmark_noinconsistent.quickstart.bed"

## Create local directory structure
mkdir -p "${OUTPUT_DIR}"
mkdir -p "${INPUT_DIR}"

# Download the data to input directory
wget -P ${INPUT_DIR} https://storage.googleapis.com/pepper-deepvariant-public/quickstart_data/HG002_ONT_2_GRCh38.chr20.quickstart.bam
wget -P ${INPUT_DIR} https://storage.googleapis.com/pepper-deepvariant-public/quickstart_data/HG002_ONT_2_GRCh38.chr20.quickstart.bam.bai
wget -P ${INPUT_DIR} https://storage.googleapis.com/pepper-deepvariant-public/quickstart_data/GRCh38_no_alt.chr20.fa
wget -P ${INPUT_DIR} https://storage.googleapis.com/pepper-deepvariant-public/quickstart_data/GRCh38_no_alt.chr20.fa.fai
wget -P ${INPUT_DIR} https://storage.googleapis.com/pepper-deepvariant-public/quickstart_data/HG002_GRCh38_1_22_v4.2.1_benchmark.quickstart.vcf.gz
wget -P ${INPUT_DIR} https://storage.googleapis.com/pepper-deepvariant-public/quickstart_data/HG002_GRCh38_1_22_v4.2.1_benchmark_noinconsistent.quickstart.bed

# Pull the docker images
sudo docker pull jmcdani20/hap.py:v0.3.12
sudo docker pull kishwars/pepper_deepvariant:r0.7-gpu

# Run PEPPER-Margin-DeepVariant
sudo docker run --ipc=host \
-v "${INPUT_DIR}":"${INPUT_DIR}" \
-v "${OUTPUT_DIR}":"${OUTPUT_DIR}" \
--gpus all \
kishwars/pepper_deepvariant:r0.7-gpu \
run_pepper_margin_deepvariant call_variant \
-b "${INPUT_DIR}/${BAM}" \
-f "${INPUT_DIR}/${REF}" \
-o "${OUTPUT_DIR}" \
-p "${OUTPUT_PREFIX}" \
-t ${THREADS} \
-r chr20:1000000-1020000 \
-g \
--ont_r9_guppy5_sup

# Run hap.py
sudo docker run -it \
-v "${INPUT_DIR}":"${INPUT_DIR}" \
-v "${OUTPUT_DIR}":"${OUTPUT_DIR}" \
jmcdani20/hap.py:v0.3.12 /opt/hap.py/bin/hap.py \
${INPUT_DIR}/${TRUTH_VCF} \
${OUTPUT_DIR}/${OUTPUT_VCF} \
-f "${INPUT_DIR}/${TRUTH_BED}" \
-r "${INPUT_DIR}/${REF}" \
-o "${OUTPUT_DIR}/happy.output" \
--pass-only \
-l chr20:1000000-1020000 \
--engine=vcfeval \
--threads="${THREADS}"

Expected output:

Type Truth
total		 True
positives		 False
negatives		 False
positives		 Recall Precision F1-Score
INDEL 2 2 0 0 1.0 1.0 1.0
SNP 39 39 39 39 1.0 1.0 1.0

Authors:

This pipeline is developed in a collaboration between UCSC genomics institute and the genomics team at Google health.