puticr is an application to identify putative Imprint Control Regions (ICRs) from Whole Genome Bisulfite Sequencing (WGBS) data. WGBS of cells representing the gametic cells (oocyte and sperm) and the three germ layer tissues- the endoderm, mesoderm, and exoderm (i.e., liver, kidney, brain, etc.) is required to identify putative ICRs.
The ICR will be identified in the following procedures:
- Identify DNA regions that have methylated ~50% in three germ layer tissues- the encoder, mesoderm, and exoderm (e.g., kidney, liver, brain, etc.).
- Identify DNA regions that have methylated ~100% in gamete cells (oocyte and sperm)
- Identify methylated regions 50% in germ layer tissues that are fully methylated (100%) in one parental allele, and the complement parental allele should be unmethylated(0%).
In other words, the framework is identifying all loci in a file (1) that are either overlap in the loci of oocyte OR sperm calls (not both)
This application generates the hotspot from germ layer tissue and gametes cells. The user has to intersect the calls from germ layer tissue, oocytes, and sperm cells to find all bona fide ICRs.
The project will streamline the analysis with most of its dependencies handled during installation.
The tool uses many python packages and other dependencies.
See the installation instructions.
Dependencies: 1. Python >= 2.7 <- Avialable in most Unix flavors 2. graphviz <- Follow your linux destro installation procidure.
Eg. In Ubuntu you do this:
sudo apt-get install graphviz
See Installation
See Changelog
The Project supports the following Python versions out of the box:
- Python >=2.7
- Work only under Unix/Linux environment, not tested on MAC
The code that makes puticr is licensed under the MIT license. Feel free to use it in your free software/open-source applications
Please report any bugs or requests that you have using the GitHub issue tracker!
Developed using Python 2.7.
- Dereje D. Jima