ipyphe

ipyphe computes and analyzes microbial colony fitness from plate images to quantify colony sizes, viability via phloxine B staining, and growth-curve metrics for functional genomics studies.

Key Features:

• Automation and Integration: Automates image acquisition, quantification, normalization, and statistical analysis for high-throughput fitness screens.
• Versatility in Data Processing: Processes colony sizes, phloxine B-derived viability scores, and growth curves from time-series data, and supports image acquisition with transilluminating flatbed scanners.
• Comprehensive Analysis Capabilities: Compares late endpoint colony-size measurements with maximum growth slopes derived from time-series analyses to provide complementary fitness metrics.
• Viability Assessment: Quantifies colony redness from phloxine B staining to produce viability scores reflecting the proportion of live cells within a colony.
• Application and Scalability: Applied to phenotype gene-deletion strains of fission yeast across 59,350 individual fitness assays under 70 different conditions, demonstrating scalability for large datasets.

Scientific Applications:

• Functional genomics phenotyping: Large-scale assessment of gene-deletion strains in fission yeast across 59,350 assays and 70 conditions to identify genetic factors influencing microbial fitness.

Methodology:

Image acquisition, image quantification, normalization, statistical analysis, time-series growth-curve analysis to extract maximum growth slopes, endpoint measurement extraction, and redness quantification of phloxine B images to compute viability scores.