Metadata-Version: 2.1
Name: ashlar
Version: 1.14.1
Summary: Alignment by Simultaneous Harmonization of Layer/Adjacency Registration
Home-page: https://github.com/sorgerlab/ashlar
Author: Jeremy Muhlich
Author-email: jeremy_muhlich@hms.harvard.edu
License: MIT License
Download-URL: https://github.com/sorgerlab/ashlar/archive/v1.14.1.tar.gz
Keywords: scripts,microscopy,registration,stitching
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Visualization
Description-Content-Type: text/x-rst
License-File: LICENSE



ASHLAR: Alignment by Simultaneous Harmonization of Layer/Adjacency Registration

Ashlar implements efficient combined stitching and registration of multi-channel
image mosaics collected using the Tissue-CycIF microscopy protocol [1]_. Although
originally developed for CycIF, it may also be applicable to other tiled and/or
cyclic imaging approaches. The package offers both a command line script for the
most common use cases as well as an API for building more specialized tools.

.. [1] Tissue-CycIF is multi-round immunofluorescence microscopy on large fixed
   tissue samples. See https://doi.org/10.1101/151738 for details.



