Pergola-ge

Pergola-ge converts longitudinal behavioral time series into genomic file structures to enable application of genomics analytical methods for interoperable and reproducible behavioral neuroscience analyses.

Key Features:

• Repurposing genomic formats: Converts behavioral time series into established genomic file structures to represent longitudinal behavioral data.
• Integration with genomics tools: Enables application of principal component analysis (PCA), hidden Markov modeling (HMM), and volcano plot analyses to behavioral datasets.
• Reproducibility and shareability: Supports scripting of public software and integration with Nextflow and containerized software to standardize computational environments for reproducible workflows.
• Cross-species proof of principle: Has been demonstrated on behavioral datasets from mice, flies, and worms.

Scientific Applications:

• Longitudinal behavioral analysis: Facilitates analysis of time series behavioral data using genomics-derived methods.
• Cross-disciplinary analysis: Enables application of genomics analytical techniques to behavioral neuroscience datasets to explore complex behaviors.
• Comparative studies: Supports reproducible analyses across model organisms including mice, flies, and worms.

Methodology:

Converts behavioral time series to genomic file structures; applies PCA, hidden Markov modeling (HMM), and volcano plot analyses; uses scripted public software and integrates with Nextflow and containerized software for reproducible workflows.