RnaChipIntegrator
is a utility that performs integrated analyses of 'gene' data (a set of genes or other genomic features) with 'peak' data (a set of regions, for example ChIP peaks) to identify the genes nearest to each peak, and vice versa.
The program was originally written specifically for ChIP-Seq and RNA-Seq data but works equally well for ChIP-chip and microarray expression data, and can also be used to integrate any set of genomic features (e.g. canonical genes, CpG islands) with peak data.
Install the latest version of the program from the Python Package Index (PyPI):
pip install RnaChipIntegrator
The simplest use of the program is:
RnaChipIntegrator GENES PEAKS
where GENES
and PEAKS
are tab-delimited files containing the 'gene' and 'peak' data respectively.
This will output two files with the nearest genes for each peak ("peak-centric" analysis), and the nearest peaks for each gene ("gene-centric" analysis).
Full documentation can be found at ReadTheDocs:
See the INSTALL
file for complete installation instructions.
The source code for the development version of the program is hosted on GitHub in the devel
branch:
and can be installed directly from GitHub using pip
:
pip install git+https://github.com/fls-bioinformatics-core/RnaChipIntegrator.git@devel
The program depends on the Python xlwt
, xlrd
and xlutils
libraries, which should be installed automatically if using pip
.
Documentation based on sphinx
is available under the docs
directory.
To build do either:
python setup.py sphinx_build
or:
cd docs
make html
both of which create the documentation in the docs/_build
subdirectory.
The Python unit tests can be run using:
python setup.py test
Note that this requires the nose
package.
Example data files can be found in the examples
subdirectory, which can be used as input to the program for test or demonstration purposes; see the README
file in the same directory for more information.
This software is licensed under the Artistic License 2.0; see the LICENSE
document.