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Isotonic Regression Based-Method in Quantitative High-Throughput Screenings for Genotoxicity.

Yosuke Fujii¹, Takeo Narita², Raymond Richard Tice³

¹Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Japan.

Dose-Response : a Publication of International Hormesis Society

|December 18, 2015

Summary

This summary is machine-generated.

Isotonic regression (IR) offers a robust alternative to the Hill equation (HE) for analyzing genotoxicity data in quantitative high-throughput screenings (qHTS). IR performs better than HE, especially with noisy or non-ideal dose-response data common in qHTS.

Keywords:

Hill equation Isotonic regression genotoxicity quantitative high-throughput screening

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Area of Science:

Toxicology
Genetics
Computational Biology

Background:

Quantitative high-throughput screenings (qHTS) are crucial for genotoxicity assessment.
The Hill equation (HE) is commonly used to analyze dose-response data, comparing wild-type and DNA repair gene knockout mutants.
HE model-fitting performs poorly with the high data variability often encountered in qHTS.

Purpose of the Study:

To evaluate the performance of isotonic regression (IR) against the Hill equation (HE) for analyzing genotoxicity dose-response data in qHTS.
To identify a more capable method for qHTS data analysis, particularly under suboptimal conditions.

Main Methods:

Applied isotonic regression (IR) to analyze quantitative high-throughput screening (qHTS) genotoxicity data.
Compared the performance of IR with the traditional Hill equation (HE) model-fitting method.
Assessed performance under various data conditions, including varying random errors and curve asymptote characteristics.

Main Results:

HE performed better than IR only when dose-response data fit HE curves with two asymptotes and had small experimental errors.
No significant difference between HE and IR was observed when experimental random errors were large.
IR demonstrated superior performance (p < 0.05) with higher specificity (96% vs. 65%) when dose-response curves lacked two asymptotes.

Conclusions:

Isotonic regression (IR) is a valuable method for analyzing genotoxicity dose-response data in quantitative high-throughput screenings (qHTS).
IR performs comparably to the Hill equation (HE) under optimal data conditions.
IR significantly outperforms HE under suboptimal or challenging data conditions frequently encountered in qHTS, enhancing genotoxicity assessment accuracy.