+description: Guided Photometry Analysis in Python, a free and open-source fiber photometry data analysis tool developed in collaboration with the Lerner Lab at Northwestern University. GuPPy provides researchers with a comprehensive pipeline for processing and analyzing fiber photometry data, including artifact correction, signal normalization, peak detection, and visualization capabilities. The Lerner Lab leads the scientific development and analysis features, while our team at CatalystNeuro focuses on the software engineering foundation that makes GuPPy sustainable and accessible. We are streamlining installation and distribution, implementing automated quality assurance, improving reliability and error handling, and enabling seamless data sharing across research platforms.
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