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Updated: Aug 13, 2025

Uncovering Beat Deafness: Detecting Rhythm Disorders with Synchronized Finger Tapping and Perceptual Timing Tasks
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DiffCircaPipeline: a framework for multifaceted characterization of differential rhythmicity.

Xiangning Xue1, Wei Zong1, Zhiguang Huo2

  • 1Department of Biostatistics, Graduate School of Public Health University of Pittsburgh, Pittsburgh, PA 15213, USA.

Bioinformatics (Oxford, England)
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Summary

We developed a new pipeline to detect multifaceted differences in circadian gene expression rhythms. This tool helps identify disrupted biological clocks linked to various diseases with improved accuracy.

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Area of Science:

  • Genomics
  • Chronobiology
  • Bioinformatics

Background:

  • Circadian gene expression rhythms govern daily physiology.
  • Disruptions in these rhythms, including altered phase, amplitude, and fitness, are implicated in numerous diseases.
  • Existing methods lack a comprehensive workflow for detecting multifaceted circadian rhythm differences with robust false positive control.

Purpose of the Study:

  • To introduce a comprehensive and interactive pipeline for systematic detection of multifaceted differential circadian rhythm characteristics.
  • To provide accurate false positive control in the analysis of circadian biomarkers.
  • To facilitate the exploration and visualization of complex circadian data.

Main Methods:

  • Development of a novel computational pipeline integrating R package and Shiny app.
  • Implementation of methods for detecting differential phase, amplitude, and rhythm fitness in gene expression data.
  • Incorporation of informative visualization and interactive exploration tools.

Main Results:

  • The pipeline successfully captures multifaceted characteristics of differentially rhythmic biomarkers.
  • Demonstrated utility through multiple case studies.
  • The workflow is designed for extensibility to various omics applications.

Conclusions:

  • The proposed pipeline offers a systematic approach to analyzing disrupted circadian rhythms.
  • It enhances the ability to identify disease-associated circadian alterations.
  • The tool provides valuable insights into the complex nature of circadian dysregulation.