Release: | 0.0.1alpha |
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Homepage: | http://slipguru.disi.unige.it/Software/PyCGH |

Repository: | https://bitbucket.org/slipguru/pycgh |

**PyCGH** is a Python library for the analysis of aCGH data.
It consists mainly of three components:

- A script which creates synthetic aCGH data, for testing purposes.
- A python wrapper for the
CGHNormaliteralgorithm [CGHNormaliter], a preprocessing step required to normalizeCGH signals.- eFLLat, an algorithm which uses a dictionary learning approach to discover common patterns in aCGH data.

**PyCGH** requires the following python libraries:

- numpy: the fundamental package for scientific computing.
- matplotlib : a plotting library.
- rpy2 : a library to include and use
Rcode in a python program.

Since the function implementing the *CGHNormaliter* algorithm is actually a wrapper for the implementation in the **R** language, an appropriate interpreter for that language is required, as well as the library containing the implementation of the algorithm itself, which can be found at this link.

In this Section an overview of each component will be given.

[CGHNormaliter] | B. van Houte, T. Binsl, H. Hettling, W. Pirovano and J. Heringa. CGHnormaliter: an iterative strategy to enhance normalization of array CGH data with imbalanced aberrations. BMC Genomics, 2009. |