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 >=3.5; installed driver version >= 450.80.02

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 --runtime=nvidia when running docker run, or the parameter --nv when running singularity run, respectively.

Prepare, install nvidia docker runtime (on host), e.g. for ubuntu:


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

sudo apt-get install nvidia-docker2 sudo pkill -SIGHUP dockerd

Or follow instruction from https://github.com/NVIDIA/nvidia-docker

### Pull prepared image ###

docker pull gglyptodon/helixer-docker:helixer_v0.3.3_cuda_11.8.0-cudnn8

run container interactively

docker run --runtime=nvidia -it gglyptodon/helixer-docker:helixer_v0.3.3_cuda_11.8.0-cudnn8

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 --runtime=nvidia -it --name helixer_testing_v0.3.3_cuda_11.2.0-cudnn8 --rm --mount type=bind,source="$(pwd)"/data,target=/home/helixer_user/shared gglyptodon/helixer-docker:helixer_v0.3.3_cuda_11.8.0-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_v0.3.3 --rm .


- Run:

docker run --runtime=nvidia -it --name helixer_v0.3.3 --rm --mount type=bind,source="$(pwd)"/data,target=/home/helixer_user/shared helixer_v0.3.3: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.

-----------------------------------

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_v0.3.3_cuda_11.8.0-cudnn8

in this example, the directory "helixer_test" already contains downloaded data

singularity run --nv helixer-docker_helixer_v0.3.3_cuda_11.8.0-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

gglyptodon / helixer-docker

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