mpaya/epigenomics_jupyter repository overview

==> Pipeline for Epigenomics data analysis

For more details, visit GitHub⁠

This image containing Jupyter Lab is prepared to run the second part of the Epigenomics Data Analysis started in Galaxy⁠ using three notebooks⁠, which have a preview of results from each command cell. They run the following steps:

• ChIP-Seq:
  • Comparison of ChIP-Seq samples with MAnorm
  • Peak annotation
  • Metagene/heatmap plots of read distribution on genes
• Complete dataset:
  • Functional annotation of results
  • Combination of ChIP-Seq and RNA-Seq results
  • Generation of tables and figures

⁠Instructions to run Jupyter notebooks

A container with steps to finalize data analysis is run mapping the directory containing the results from Galaxy workflows to a work directory that can be accessed by Jupyter. Thus, results after Galaxy serve as input for Jupyter. Required annotation files should be copied to a folder accessible by Jupyter (in the example, analysis/lib). Notebooks are in a separate location and steps are prepared to run all cells from each notebook by order of numbering.

⁠Prepare environment

Here, the same default port of Jupyter is mapped locally. If using another local instance of jupyter, modify the port to avoid clashes.

local_path=~/DockerFolders/run_v1   # name for the export directory
jup_name=nb1                        # name of container
jup_port=8888                       # local port where Jupyter is run

⁠Download and activate the container

docker run \
-p $jup_port:8888 \
--name $jup_name \
-v "${local_path}"/analysis:/home/jovyan/work \
mpaya/epigenomics_jupyter:2.5

After running for the first time, Jupyter prints a link with the host address and a token to facilitate opening the web browser. Access to Jupyter may be also controlled from this screen, terminating with CTRL+C to close the session. On subsequent sessions of the same container, no output is printed to the terminal and the token has to be retrieved manually.

⁠List running notebooks and tokens

This step is required since a new token is generated each time the container is started (docker start ${jup_name}"), in case the window does not autolaunch or on a remote terminal.

docker exec -it "${jup_name}" bash
jupyter notebook list

The notebooks and galaxy results are on their own folders. On the first notebook, an instruction indicates where Jupyter results will reside.

⁠Save notebooks

Initially, notebooks are on a folder inside the container. To save it to your local system, select 'Save Notebook As...' and change 'notebooks' for 'work' on the pop7up window for them to be saved with the rest of results.

⁠Stop container when finished

docker stop "${jup_name}"

⁠Cleanup

After data analysis has finished and results are properly stored, folders linking to the docker container may be deleted.

# delete results
sudo rm -rf ~/DockerFolders/"${dir_name}"/analysis/jupyter-res

⁠Reproducible Brassica rapa data analysis

This image also contains Jupyter notebooks that reflect the data analysis performed on the paper with doi: 10.1093/gigascience/giz147⁠. If running this analysis, the container needs to be mapped to the brassica analysis folder, such as:

docker run \
-p $jup_port:8888 \
--name $jup_name \
-v "${local_path}"/bra_analysis:/home/jovyan/work \
mpaya/epigenomics_jupyter:2.5

Notebooks may be found in ~/work.