pyaffy

pyAffy: Processing raw data from Affymetrix expression microarrays in Python.


Keywords
affymetrix, microarray, rma, expression, normalization
License
GPL-3.0
Install
pip install pyaffy==0.3.2

Documentation

pyAffy

pyAffy is a Python/Cython implementation of the RMA algorithm for processing raw data from Affymetrix expression microarrays. For a detailed discussion of this implementation, see the pyAffy PeerJ preprint. For a list of changes, see the changelog.

Installation

Option 1: Using pip

$ pip install pyaffy

Option 2: Cloning the GitHub repository

$ git clone https://github.com/flo-compbio/pyaffy.git
$ cd pyaffy
$ pip install -e .

Usage

The rma function expects two parameters: A custom CDF file (from the Brainarray web site) and an ordered dictionary (collections.OrderedDict) with sample names as keys and corresponding CEL files as values.

The rma function returns a list of genes, a list of samples, and an expression matrix (of type numpy.ndarray), in that order.

from pyaffy import rma
# for documentation of the rma function, try:
# help(rma)
genes, samples, X = rma(cdf_file, sample_cel_files)

A small example with real code is available in the pyaffy-demos repository.

Copyright and License

Copyright (c) 2016 Florian Wagner

pyAffy is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License, Version 3,
as published by the Free Software Foundation.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.