Tfisher: A powerful truncation and weighting procedure for combining p-values

Hong Zhang, Tiejun Tong, John Landers, Zheyang Wu

Research output: Contribution to journalJournal articlepeer-review

10 Citations (Scopus)


The p-value combination approach is an important statistical strategy for testing global hypotheses with broad applications in signal detection, meta-analysis, data integration, etc. In this paper we extend the classic Fisher’s combination method to a unified family of statistics, called TFisher, which allows a general truncation-and-weighting scheme of input p-values. TFisher can significantly improve statistical power over the Fisher and related truncation-only methods for detecting both rare and dense “signals.” To address wide applications, analytical calculations for TFisher’s size and power are deduced under any two continuous distributions in the null and the alternative hypotheses. The corresponding omnibus test (oTFisher) and its size calculation are also provided for data-adaptive analysis. We study the asymptotic optimal parameters of truncation and weighting based on Bahadur efficiency (BE). A new asymptotic measure, called the asymptotic power efficiency (APE), is also proposed for better reflecting the statistics’ performance in real data analysis. Interestingly, under the Gaussian mixture model in the signal detection problem, both BE and APE indicate that the soft-thresholding scheme is the best, the truncation and weighting parameters should be equal. By simulations of various signal patterns, we systematically compare the power of statistics within TFisher family as well as some rare-signal-optimal tests. We illustrate the use of TFisher in an exome-sequencing analysis for detecting novel genes of amyotrophic lateral sclerosis. Relevant computation has been implemented into an R package TFisher published on the Compre-hensive R Archive Network to cater for applications.

Original languageEnglish
Pages (from-to)178-201
Number of pages24
JournalAnnals of Applied Statistics
Issue number1
Publication statusPublished - Mar 2020

Scopus Subject Areas

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty

User-Defined Keywords

  • Genetic association studies
  • Global hypothesis testing
  • Optimal test
  • P-value combination
  • Signal detection
  • Statistical power


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