Metadata-Version: 2.1
Name: gecos
Version: 0.2.3
Summary: Generated color schemes for sequence alignment visualizations
Home-page: UNKNOWN
Author: Patrick Kunzmann
Author-email: padix.key@gmail.com
License: BSD 3-Clause
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.6
Requires-Dist: biotite
Requires-Dist: numpy
Requires-Dist: scikit-image


Generated color schemes for sequence alignment visualizations
=============================================================

Multiple sequence alignments are often visualized by coloring the
symbols according to some kind of properties.
For example a color scheme for amino acids could use one color for
hydrophobic residues, another color for positively charged residues
and so forth.
Usually, such color schemes are created manually by experienced people
who have knowledge about the characteristics of the e.g. amino acids,
so they can assign equal or similar colors to amino acids that share
similar properties.

The *Gecos* software follows a different approach:
Instead of looking at specific, sometimes subjective properties,
it uses another source for estimating the similarity of symbols:
the substitution matrix itself.
Similar colors are assigned to high scoring pairs of symbols, low
scoring pairs get distant colors - in a completely automatic manner.
As a result the distance of two symbols in the substitution matrix
corresponds to the perceptual differences in the color scheme.


