PRECOG

PRECOG analyzes high-resolution microbial growth data to extract standardized phenotypic traits and fitness components for microbial phenomics and functional genomics studies.

Key Features:

• Quality Control and Data Filtering: Implements quality indices to distinguish high-quality growth experiments from low-quality ones and reduce false positives.
• Pre-processing Filters: Applies computationally efficient pre-processing filters that are comparable in function to more complex neural network procedures to handle non-standard growth dynamics.
• Phenotypic Trait Extraction and Visualization: Extracts phenotypic traits from population size growth data and provides visualization for exploration and evaluation.
• Standardization in Data Analysis: Standardizes data calibration, project design parameters, and feature extraction to ensure consistent estimation of growth traits.
• Phenomics Database Construction: Supports creation of standardized phenomics databases aggregating microbial growth and trait data.

Scientific Applications:

• Microbial phenomics: Captures and quantifies variations in growth phenotypes across genetic, epigenetic, and environmental contexts.
• Functional genomics: Links growth-derived phenotypes to genetic and epigenetic variation for functional genomics analyses.
• Fitness estimation: Extracts fitness components from population size growth trajectories.
• Cross-study comparisons: Enables aggregation of standardized growth traits in phenomics databases for comparative analyses across studies.

Methodology:

Implements quality indices for experiment filtering, computationally efficient pre-processing filters comparable to neural network procedures, standardized data calibration and feature extraction for phenotypic trait extraction, and generation of phenomics databases.