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