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diproperm: An R Package for the DiProPerm Test.

Andrew G Allmon1, J S Marron1, Michael G Hudgens1

  • 1University of North Carolina at Chapel Hill, Department of Biostatistics.

The R Journal
|June 20, 2022
PubMed
Summary
This summary is machine-generated.

The direction-projection-permutation (DiProPerm) test precisely compares high-dimensional data distributions, even with few samples. An R package is now available to apply this exact statistical test in biomedical research.

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Area of Science:

  • Biostatistics
  • Computational Biology
  • Genomics

Background:

  • High-dimensional low sample size (HDLSS) data presents unique challenges in statistical analysis.
  • Comparing distributions in HDLSS settings requires robust and accurate methods.
  • Existing methods may not adequately control Type I error rates in HDLSS scenarios.

Purpose of the Study:

  • To introduce the direction-projection-permutation (DiProPerm) test for comparing two high-dimensional distributions.
  • To present the diproperm R package for implementing the DiProPerm test.
  • To demonstrate the practical application of the DiProPerm test using real-world biomedical data.

Main Methods:

  • The DiProPerm test utilizes a direction-projection-permutation strategy for hypothesis testing.
  • The test is designed to be exact, ensuring Type I error control.
  • Implementation is facilitated through the newly developed diproperm R package.

Main Results:

  • The DiProPerm test provides an exact two-sample hypothesis test for high-dimensional data.
  • The test guarantees Type I error control at the nominal level, irrespective of sample size.
  • The diproperm R package enables straightforward application of the DiProPerm test.

Conclusions:

  • The DiProPerm test is a powerful and reliable tool for analyzing HDLSS data in biomedical research.
  • The availability of the diproperm R package lowers the barrier for researchers to utilize this advanced statistical method.
  • Accurate comparison of high-dimensional distributions is crucial for advancing biomedical discoveries.