helixer-docker

This repository accompanies https://github.com/weberlab-hhu/Helixer .

The aim is to provide a mostly hassle-free way to use Helixer via docker (or singularity).

For more information on how to run Helixer, please refer to its documentation.

---

Instructions for docker (for use with Nvidia GPUs)

• Prerequisites (on host):
  • Nvidia GPU with CUDA capabilities >=6.1; installed driver version >=525.60.13

Note that the code will run on the CPU if an Nvidia GPU or appropriate drivers are not available. However, the walltime requirements will increase substantially. If not running on the GPU exclude the parameter --gpus all when running docker run, or the parameter --nv when running singularity run, respectively.

• Prepare, install Docker (https://docs.docker.com/engine/install/ubuntu/) and the Nvidia Container Toolkit (https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) (on host), e.g. for ubuntu. Please also be aware of Dockers Firewall limitations mentioned on the installation instructions website.

##################
# install Docker #
##################

# Add Docker's official GPG key:
sudo apt-get update
sudo apt-get install ca-certificates curl
sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc

# Add the repository to Apt sources:
echo \
  "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \
  $(. /etc/os-release && echo "$VERSION_CODENAME") stable" | \
  sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo apt-get update

# install the latest Docker packages
sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

# verify Docker installation
sudo docker run hello-world

####################################
# install Nvidia Container Toolkit #
####################################

# configure the production repository
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
  && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
    sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
    sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

# update the packages list from the repository
sudo apt update

# install the NVIDIA Container Toolkit packages
sudo apt-get install -y nvidia-container-toolkit

####################
# configure Docker #
####################

# configure the container runtime
sudo nvidia-ctk runtime configure --runtime=docker

# restart the Docker daemon
sudo systemctl restart docker

# Hint: you can also configure Docker in rootless mode (see the Nvidia Container Toolkit installation instructions website)

Note: The Nvidia-Docker wrapper (https://github.com/NVIDIA/nvidia-docker) has been deprecated. It is recommended to switch to the Nvidia Container Toolkit to use Helixer via Docker.

Pull prepared image

docker pull gglyptodon/helixer-docker:helixer_v0.3.4_cuda_12.2.2-cudnn8
# run container interactively 
docker run --gpus all -it gglyptodon/helixer-docker:helixer_v0.3.4_cuda_12.2.2-cudnn8

(Note: nvidia-docker v2 uses --runtime=nvidia instead of --gpus all)

# additionally, set up a shared directory and mount it, e.g.:
# on host:
mkdir -p data/out
chmod o+w data/out # something the container can write to
# mount directory and run interactively:
docker run --gpus all -it --name helixer_testing_v0.3.4_cuda_12.2.2-cudnn8 --rm --mount type=bind,source="$(pwd)"/data,target=/home/helixer_user/shared gglyptodon/helixer-docker:helixer_v0.3.4_cuda_12.2.2-cudnn8

Alternatively, build it yourself

• Build:

mkdir SOME_DIR
cd SOME_DIR
wget https://raw.githubusercontent.com/gglyptodon/helixer-docker/main/Dockerfile

mkdir -p data/out
chmod o+w data/out # something the container can write to

docker build -t helixer_v0.3.4 --rm .

• Run:

docker run --gpus all -it --name helixer_v0.3.4 --rm --mount type=bind,source="$(pwd)"/data,target=/home/helixer_user/shared helixer_v0.3.4:latest

Try out:

# Download models (models will be saved to ~/.local/share/Helixer/models/ )
helixer_user@03356047d15f:~$ Helixer/scripts/fetch_helixer_models.py
helixer_user@03356047d15f:~$ cd shared/out/

# get some test data
helixer_user@03356047d15f:~/shared/out$ curl -L ftp://ftp.ensemblgenomes.org/pub/plants/release-47/fasta/arabidopsis_lyrata/dna/Arabidopsis_lyrata.v.1.0.dna.chromosome.8.fa.gz --output Arabidopsis_lyrata.v.1.0.dna.chromosome.8.fa.gz

# predict gene models
helixer_user@03356047d15f:~/shared/out$ Helixer.py --fasta-path Arabidopsis_lyrata.v.1.0.dna.chromosome.8.fa.gz --lineage land_plant --gff-output-path Arabidopsis_lyrata_chromosome8_helixer.gff3

# see start and end of expected output below:

# No config file found

# Helixer.py config: 
# {'batch_size': 32,
# 'compression': 'gzip',

# [...]

# Total: 12727167bp across 2300 windows

# Helixer successfully finished the annotation of Arabidopsis_lyrata.v.1.0.dna.chromosome.8.fa.gz in 0.06 hours. GFF file written to Arabidopsis_lyrata_chromosome8_helixer.gff3.

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Notes on running via Singularity

Installing Singularity

( If you already have singularity available, skip to section "Running via Singularity" below.)

For singularity install, see also: https://github.com/sylabs/singularity/blob/master/INSTALL.md

Install go:

export VERSION=1.18.1 OS=linux ARCH=amd64  # change this as you need

wget -O /tmp/go${VERSION}.${OS}-${ARCH}.tar.gz \
  https://dl.google.com/go/go${VERSION}.${OS}-${ARCH}.tar.gz
sudo tar -C /usr/local -xzf /tmp/go${VERSION}.${OS}-${ARCH}.tar.gz

echo 'export PATH=$PATH:/usr/local/go/bin' >> ~/.bashrc
source ~/.bashrc

Clone syslabs' singularity repo and install:

mkdir  -p github.com/syslabs/
cd github.com/syslabs
git clone --recurse-submodules https://github.com/sylabs/singularity.git
cd singularity/
git checkout --recurse-submodules v3.9.9

./mconfig
make -C builddir
sudo make -C builddir install

If all went well, you should be able to see a version number:

singularity --version
# -->  singularity-ce version 3.9.9

Running via Singularity

# pull current docker image 
singularity pull  docker://gglyptodon/helixer-docker:helixer_v0.3.4_cuda_12.2.2-cudnn8

# in this example, the directory "helixer_test" already contains downloaded data
singularity run --nv helixer-docker_helixer_v0.3.4_cuda_12.2.2-cudnn8.sif Helixer.py --fasta-path helixer_test/Arabidopsis_lyrata.v.1.0.dna.chromosome.8.fa.gz --lineage land_plant --gff-output-path Arabidopsis_lyrata_chromosome8_helixer.gff3
# notice '--nv' for GPU support