RCAT

RCAT extracts rhythmic components such as period, amplitude, and phase from time-series datasets to analyze circadian clock gene expression and dynamics measured by NGS, microarray, RNA-Seq, and real-time luminescence/fluorescence reporting systems.

Key Features:

• Rhythmic component extraction: Computes period, amplitude, and phase from time-series expression and protein-level data.
• Input data types: Accepts time-series data from next-generation sequencing (NGS), microarray, RNA-Seq, Lumicycle® luminometer real-time fluorescence/luminescence recordings, and synthetic datasets from CircaInSilico.
• Quality estimation: Reports relative amplitude error (RAE) as a criterion for result quality assessment.
• Output formats: Produces tabular and visual outputs and saves results as CSV files for downstream analysis.
• Benchmarking and robustness: Validated with synthetic genome biology data from CircaInSilico across varying collection intervals and amplitude ranges.

Scientific Applications:

• Microarray and RNA-Seq analysis: Identification of core clock genes with significant periodicity from Gene Expression Omnibus (GEO) liver tissue datasets.
• Real-time fluorescence/luminescence reporting: Computation of period, amplitude, and phase from Lumicycle® luminometer recording datasets to analyze dynamic circadian responses.

Methodology:

Extraction of rhythmic components from time-series datasets using statistical analysis, with benchmarking against synthetic data from CircaInSilico and application to experimental NGS, microarray/RNA-Seq, and Lumicycle® time-series data.