BEAN-counter

BEAN-counter processes and analyzes barcode sequencing data from multiplexed pooled experiments to enable high-throughput fitness profiling and chemical-genetic interaction analysis.

Key Features:

• High-throughput processing: Handles large volumes of barcode sequencing data generated by multiplexed experiments.
• Cross-organism applicability: Applied to mutant collections from Saccharomyces cerevisiae, Schizosaccharomyces pombe, Escherichia coli, and Zymomonas mobilis.
• Demonstrated scalability: Supported analysis of approximately 4 million chemical-by-mutant combinations across seven diverse compound collections and nearly 14,000 chemical compounds.
• Data processing and interaction scoring: Performs processing of barcode sequencing reads and scoring of genetic and chemical-genetic interactions.
• Experiment design support: Provides a structured approach for designing large-scale, multiplexed barcode sequencing experiments.
• Implementation: Implemented in Python.

Scientific Applications:

• Fitness profiling of pooled mutant collections: Quantitative assessment of mutant fitness across pooled conditions using barcode counts.
• Large-scale chemical-genetic interaction screening: Analysis of chemical-by-mutant interaction matrices at the scale of millions of combinations and thousands of compounds.
• Cross-species barcode sequencing studies: Comparative and functional studies across yeast and bacterial mutant collections.

Methodology:

Processes multiplexed barcode sequencing data and performs interaction scoring, and encapsulates accumulated analysis methods for designing and analyzing large-scale pooled barcode sequencing experiments.