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CMSIP: Hydroxymethylation anlaysis of CMS-IP data

A scalable, accurate, and efficient solution for hydroxymethylation analysis of CMS-IP sequencing data.

Workflow of CMSIP.

Installation

CMSIP has been deployed in Bioconda at https://anaconda.org/bioconda/cmsip. It is encouraged to install CMSIP from Bioconda due to most runtime dependencies will be installed automatically. The following channels should be added in Conda. Namely,

conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge
conda install cmsip

Alternatively, CMSIP has been also deployed in PyPI at https://pypi.org/project/cmsip, and it can be installed via pip.

pip3 install cmsip

In some cases, users want to build CMSIP manually from source code at https://github.com/lijinbio/cmsip. Below is an example installation steps.

git clone https://github.com/lijinbio/cmsip.git
cd cmsip
python3 setup.py install

In order to run CMSIP after a manual installation, the following dependent softwares are required.

Software URL
Python 3 https://www.python.org
Matplotlib https://matplotlib.org
PyYAML https://pyyaml.org
bedtools https://bedtools.readthedocs.io
R software https://www.r-project.org
R package DESeq2 https://bioconductor.org/packages/release/bioc/html/DESeq2.html
R package genefilter https://bioconductor.org/packages/release/bioc/html/genefilter.html
R package RVAideMemoire https://cran.r-project.org/web/packages/RVAideMemoire/index.html
Gawk https://www.gnu.org/software/gawk
MOABS https://github.com/sunnyisgalaxy/moabs

Documentation

CMSIP takes in a configuration file for input data and program parameters. CMSIP can be run end-to-end, starting from raw FASTQ files to peak calling and differential hydroxymethylation identification. One can also start the pipeline from intermediate steps. For example, using alignment files as input so that mapping steps will be skipped.

Example configuration file

An example configuration is cms.yaml under the root of https://github.com/lijinbio/cmsip.

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