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A comparison of methods to control type I errors in microarray studies.

Jinsong Chen1, Mark J van der Laan, Martyn T Smith

  • 1Lawrence Berkeley National Laboratory. jchen@lbl.gov

Statistical Applications in Genetics and Molecular Biology
|December 7, 2007
PubMed
Summary
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For microarray studies, the quantile-transformed-bootstrap-distribution (QTBD) method offers superior control of family-wise error rates (FWER) and gene discovery power. This resampling method outperforms permutation and null-centered and scaled bootstrap (NCSB) approaches in general circumstances.

Area of Science:

  • Genomics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Microarray studies require robust multiple testing procedures to identify differentially expressed genes.
  • Accurate control of error rates and high statistical power are critical challenges in analyzing large-scale gene expression data.
  • Existing resampling methods like permutation, NCSB, and QTBD have theoretical advantages and limitations.

Purpose of the Study:

  • To compare the practical performance of three resampling-based multiple testing methods: permutation, null-centered and scaled bootstrap (NCSB), and quantile-transformed-bootstrap-distribution (QTBD).
  • To evaluate the control of family-wise error rates (FWER) and statistical power of these methods through data simulations.
  • To determine which method provides the most accurate and powerful control of error rates in microarray data analysis.

Related Experiment Videos

Main Methods:

  • Data simulations were used to compare the performance of permutation, NCSB, and QTBD methods.
  • The primary metric for comparison was the control of family-wise error rates (FWER).
  • Statistical power, defined as the ability to detect truly differentially expressed genes, was also assessed.

Main Results:

  • Permutation methods may fail to control Type I errors when subset pivotality is violated.
  • The NCSB method requires a large number of bootstrap samples for adequate error control.
  • The QTBD method demonstrated accurate Type I error control with fewer restrictions and showed relatively accurate and powerful performance in general circumstances.

Conclusions:

  • The QTBD method is a promising approach for multiple testing in microarray studies due to its robust error control.
  • QTBD offers a more reliable and powerful solution compared to traditional permutation and NCSB methods.
  • This study highlights the importance of selecting appropriate multiple testing procedures for maximizing discoveries in gene expression analysis.