https://github.com/deib-geco/pygmql
Python Library for data analysis based on GMQL
https://github.com/deib-geco/pygmql
anaconda bedtools big-data binder bioinformatics bioinformatics-analysis bioinformatics-pipeline bioinformatics-tool genomics gmql java jupyter-notebook pypi python scala
Last synced: about 1 month ago
JSON representation
Python Library for data analysis based on GMQL
- Host: GitHub
- URL: https://github.com/deib-geco/pygmql
- Owner: DEIB-GECO
- License: apache-2.0
- Created: 2017-03-23T10:28:05.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2021-12-01T09:50:29.000Z (over 3 years ago)
- Last Synced: 2025-04-08T23:13:10.408Z (about 1 month ago)
- Topics: anaconda, bedtools, big-data, binder, bioinformatics, bioinformatics-analysis, bioinformatics-pipeline, bioinformatics-tool, genomics, gmql, java, jupyter-notebook, pypi, python, scala
- Language: Python
- Homepage:
- Size: 43.4 MB
- Stars: 14
- Watchers: 11
- Forks: 5
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- Changelog: change_remote_instance.sh
- License: License.txt
Awesome Lists containing this project
README
# PyGMQL
API for calling interactively the GMQL Engine from Python
[](https://travis-ci.org/DEIB-GECO)
[](https://badge.fury.io/py/gmql)
[](https://github.com/DEIB-GECO/PyGMQL)
[](https://codecov.io/gh/DEIB-GECO/PyGMQL)
## Documentation
The doucumentation can be found at the following link: http://pygmql.readthedocs.io
[](http://pygmql.readthedocs.io/en/latest/?badge=latest)
## Examples
In the [examples folder](./examples) are available the Notebooks and the scripts to reproduce the analysis presented in the manuscript.
## Docker image
If you want to run some of the examples provided in the example folder you can directly install the PyGMQL docker image.
```
docker pull gecopolimi/pygmql
```
You can run the docker instance using the following command:
```
docker run --rm \
--name pygmql_instance \
-p :8888 \
gecopolimi/pygmql
```
where you can set `` to any free port number on your machine.
This will start a Jupyter Lab server which will run at the address
```
https://localhost:
```
Inside the docker you will find the `example` folder containing both notebooks and scripts.
## Get in touch
You can ask questions or provide some feedback through our Gitter channel.
[](https://gitter.im/DEIB-GECO/PyGMQL?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
## Requirements
The library requires the following:
* Python 3.4+
* The latest version of JAVA installed
* The JAVA_HOME variable set to the Java installation folder (example: `C:\Program Files\Java\jdk1.8.0_161` or `~/jdk1.8.0_161`)
## Installation
### From github
First of all download this repository in a choosen location:
```
git clone https://github.com/DEIB-GECO/PyGMQL.git
```
Than go inside the library folder and install the package as follows:
```
cd PyGMQL
pip install -e .
```
### From PyPi
```
pip install gmql
```
## Setup
### Use Anaconda
We suggest to manage your python distribution through Anaconda.
The latest version of can be downloaded from https://www.continuum.io/downloads.
Once your Anaconda distribution is installed, let's create a brand new environment:
```
conda create --name pygmql python=3
```
### Check if JAVA is installed
Check that the `JAVA_HOME` enviroment variable is correctly set to
the latest JAVA distribution.
```
echo $JAVA_HOME
```
If the variable is not set (the previous command does not show nothing), you may need
to install JAVA (https://www.java.com/it/download/) and then set `JAVA_HOME` like the following:
On linux:
```
echo export "JAVA_HOME=/path/to/java" >> ~/.bash_profile
source ~/.bash_profile
```
On Mac:
```
echo export "JAVA_HOME=\$(/usr/libexec/java_home)" >> ~/.bash_profile
source ~/.bash_profile
```
On Windows:
1. Right click My Computer and select Properties.
2. On the Advanced tab, select Environment Variables, and then
edit JAVA_HOME to point to where the JDK software is located,
for example, C:\Program Files\Java\jdk1.6.0_02.
### Use it in Jupyter Notebooks
We strongly suggest to use the library with the support of a **Jupyter Notebook**
for the best graphical rendering of the data structures.
It may be necessary to manually install the Jupyter kernel:
```
source activate pygmql
python -m ipykernel install --user --name pygmql --display-name "Python (pygmql)"
```
### Keep the code updated
This is a constantly evolving project. Therefore the library will be
constantly added with new features. Therefore we suggest to update your
local copy periodically:
```
cd PyGMQL
git pull
```