Statistical significance of combinatorial regulations

Proc Natl Acad Sci U S A. 2013 Aug 6;110(32):12996-3001. doi: 10.1073/pnas.1302233110. Epub 2013 Jul 23.

Abstract

More than three transcription factors often work together to enable cells to respond to various signals. The detection of combinatorial regulation by multiple transcription factors, however, is not only computationally nontrivial but also extremely unlikely because of multiple testing correction. The exponential growth in the number of tests forces us to set a strict limit on the maximum arity. Here, we propose an efficient branch-and-bound algorithm called the "limitless arity multiple-testing procedure" (LAMP) to count the exact number of testable combinations and calibrate the Bonferroni factor to the smallest possible value. LAMP lists significant combinations without any limit, whereas the family-wise error rate is rigorously controlled under the threshold. In the human breast cancer transcriptome, LAMP discovered statistically significant combinations of as many as eight binding motifs. This method may contribute to uncover pathways regulated in a coordinated fashion and find hidden associations in heterogeneous data.

Keywords: Bonferroni correction; gene expression.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Breast Neoplasms / genetics
  • Breast Neoplasms / physiopathology
  • Computational Biology / methods*
  • Female
  • Gene Expression Profiling / methods
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks / genetics
  • Gene Regulatory Networks / physiology
  • Humans
  • Models, Genetic
  • Reproducibility of Results
  • Signal Transduction / genetics
  • Signal Transduction / physiology*
  • Transcription Factors / genetics
  • Transcription Factors / metabolism*

Substances

  • Transcription Factors