Skip to content

Latest commit

 

History

History
175 lines (140 loc) · 4.8 KB

README.md

File metadata and controls

175 lines (140 loc) · 4.8 KB
Raw

This is a README describes this repository, which contains any code related to testing and benchmarking BAM file compression, using various technologies.

Structure

Below is the directory structure and the content of the folder:

Access
|____wrappers
|____envs
|____docker
|____cloud_services
|____CHANGELOG.md
|____README.md
|____workflow
|____rules
| |____BAM
| |____CRAM
|____.gitlab-ci.yaml
|____conf
|____reports
|____src

Figure 1: Directory structure of the repository.

Content

Table 1: Content of the different folders (Fig. 1).

Folder Content
wrappers wrapper scripts to launch docker containers
docker Dockerfiles building Docker images
envs .yaml files conda environments
cloud_services launcher scripts for cloud services
workflow Snakemake workflow files
rules Snakemake rules, furter separated into different functionalities
conf Snakemake .json conf files
reports Snakemake benchmark reports
src ad-hoc/custom scripts

In the future, this repository can be used to create dedicated forks for processes that may become more complex, e.g. "Concordance" can be spun out as a separate repo, in the future.

Dependencies

Below are the dependencies required:

  1. Linux/Unix- like environment
  2. git installation
  3. python3
  4. conda (python package)
  5. docker (optional, if using conda directly)

Clone git repository

One would need to clone the entire Access gitlab directory in order to execute this workflow.

Via https:

git clone https://gitlab.com/Narayanasamy_1985/Access.git

or Via ssh:

git clone [email protected]:megeno_development/Access.git <dir_name>

Replace <dir_name> with your own directory name.

If you already have a git directory named "Access", then use:

Go into the relevant directory:

cd <your local directory>/Access

NOTE: Always work on the dev branch or other feature branches when developing. Change to dev branch (master has to be cleaned up)

git checkout dev

Own environment

Install all the necessary tools.

  1. Python 3
  2. conda, anaconda
  3. other tools (TBD)

Once you have conda, you can simply use the .yaml files in the docker folder and run:

conda update -n base -c defaults conda
conda env create --file envs/requirements.yaml --prefix <your favourite install path>

You should have all the necessary files required. Now, load the environment and start running:

source activate py36

NOTE: For now, we decided to use only python 3.

Docker

If you do not want to install these tools in a conda virtual environment, then you can run a docker container to test it. You can either build the docker container yourself or pull an existing one from the Dockerhub`

Building your own.

If you wish to build your own container to test some specific programs. First go to the docker folder and build the container. Run the command(s) below:

cd docker

docker build -f <location of the docker file>/Dockerfile . -t megeno/compression:latest

Name the as you like. This should be formalized in the future.

Now, you are free to run your docker image. Named latest here.

$ docker run --privileged -v /home/emad/.config/rclone/rclone.conf:/root/.rclone.conf -v /home/emad/projects/compression/:/code/ -v /work/compression_tests:/home/Archive/Compression -v /work/data/:/home/Archive/Data/ -v /work/analysis/ -v /work/references/:/references/ --rm -it megeno/compression

Pull from DockerHub

To be updated

Snakemake

Once you have your environment setup, you can now run the pipeline.

snakemake -pks workflow/master.workflow --configfile config/oci_config Compression/checkpoints/all.done

NOTE: Please ignore the parts below for now. I will spin it out to a different document.

Transfer tests

This workflow is used to test and benchmark the upload transfer times.

Use the handy-dandy wrapper script

Example:

wrappers/run.sh

Docker and a handy-dandy wrapper script

Example:

$ docker run --privileged -v /home/emad/.config/rclone/rclone.conf:/root/.rclone.conf -v /home/emad/projects/compression/:/code/ -v /work/compression_tests:/home/Archive/Compression -v /work/data/:/home/Archive/Data/ -v /work/analysis/ -v /work/references/:/references/ --rm -it megeno/compression <wrapper.sh>

Virtual environment python

Steps are being documented https://docs.google.com/document/d/1u6UHIJ3CSVKpkaeRxlcFkrlgP79B7aL9vMpeV8XfoIk/edit#

conda activate compression

Dry run for everything

snakemake -npks workflow/master.workflow --configfile config/oci_config Compression/checkpoints/all.done

Dry run for only cram

snakemake -npks workflow/master.workflow --configfile config/oci_config Compression/checkpoints/cram.done

End virtual environment

conda deactivate