CIRCUST

CIRCUST reconstructs temporal order of circadian gene expression from single-timepoint transcriptomic data to quantify near-24-hour molecular rhythms across human tissues.

Key Features:

• Circular statistics: Uses circular-statistics methods to model and analyze near-24-hour oscillatory gene expression patterns.
• Noise robustness: Handles noisy single-timepoint gene expression data and unknown sampling times to enable temporal reconstruction from sparse datasets.
• Minimal assumptions: Operates without assuming rhythmic gene evolutionary conservation across tissues, increasing applicability across diverse tissue types.

Scientific Applications:

• Human circadian expression atlas: Enables construction and characterization of daily rhythmic gene expression across 34 human tissues using the GTEx dataset.

Methodology:

CIRCUST applies circular-statistics-based analysis to reconstruct temporal order from single-timepoint gene expression data and validates robustness using controlled experiments with known sampling times.