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Cluster analysis: a simple, versatile, and robust algorithm for endocrine pulse detection.

J D Veldhuis, M L Johnson

    The American Journal of Physiology
    |April 1, 1986
    PubMed
    Summary
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    This study introduces a novel algorithm to detect episodic endocrine signals by identifying statistically significant hormone level increases and decreases. This method accurately analyzes hormone pulsatility, crucial for understanding physiological communication.

    Area of Science:

    • Endocrinology
    • Physiology
    • Computational Biology

    Background:

    • Endocrine signaling is vital for physiological communication.
    • Many crucial endocrine signals occur in episodic or pulsatile patterns.
    • Accurate detection of these pulses is essential for understanding endocrine regulation.

    Purpose of the Study:

    • To develop a versatile, statistically based computerized algorithm for investigating endocrine pulse signal regulation.
    • To define a pulse as a statistically significant increase followed by a decrease in hormone values, relative to experimental error.

    Main Methods:

    • A computerized algorithm defines endocrine pulses based on statistically significant clusters of hormone values.
    • The algorithm assesses increases and decreases relative to experimental error in nadir and peak data clusters.

    Related Experiment Videos

  • Operator can specify cluster sizes for peaks and nadirs, ensuring flexibility.

    • Main Results:

    • The algorithm is insensitive to unstable baseline hormone concentrations and varying pulse characteristics.
    • It is minimally dependent on assumptions about hormone secretion or clearance rates.
    • Validated for false-positive errors across a wide range of variations (4-52%).

    Conclusions:

    • The developed algorithm provides a robust and statistically sound method for analyzing episodic endocrine signals.
    • It accurately identifies pulsatile patterns for various hormones like LH, FSH, GH, prolactin, ACTH, and cortisol.
    • This tool aids in the study of endocrine regulation and physiological communication.