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Related Experiment Video

Updated: Jun 22, 2026

Acyl-PEGyl Exchange Gel Shift Assay for Quantitative Determination of Palmitoylation of Brain Membrane Proteins

Acyl-PEGyl Exchange Gel Shift Assay for Quantitative Determination of Palmitoylation of Brain Membrane Proteins

Published on: March 29, 2020

Fewer permutations, more accurate P-values.

Theo A Knijnenburg¹, Lodewyk F A Wessels, Marcel J T Reinders

¹Institute for Systems Biology, Seattle, WA, USA. tknijnenburg@systemsbiology.org

Bioinformatics (Oxford, England)

|May 30, 2009

Summary

This summary is machine-generated.

Permutation tests estimate statistical significance using P-values. A new tail approximation method accurately calculates P-values with fewer permutations, reducing computational cost.

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Area of Science:

Statistics
Computational Biology
Bioinformatics

Background:

Permutation tests are standard for assessing statistical significance.
P-values are calculated as the fraction of permutation values exceeding the original statistic.
Accurate estimation of small P-values requires a large number of permutations, which is computationally expensive.

Purpose of the Study:

To develop a computationally efficient method for calculating P-values from permutation tests.
To improve the accuracy of P-value estimation, especially for small values.

Main Methods:

A novel method for computing P-values using tail approximation is presented.
The tail of the permutation value distribution is approximated using a generalized Pareto distribution.

Main Results:

The proposed tail approximation method provides accurate P-value estimates.
This method significantly reduces the number of permutations required compared to standard empirical methods.
Achieves accurate P-value estimation with drastically reduced computational cost.

Conclusions:

The tail approximation method offers a computationally feasible alternative for accurate P-value estimation in permutation tests.
This approach is particularly beneficial for scenarios requiring precise estimation of small P-values.