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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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A semiparametric kernel independence test with application to mutational signatures.

DongHyuk Lee1, Bin Zhu1

  • 1Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Journal of the American Statistical Association
|May 6, 2022
PubMed
Summary

A new statistical test, SKIT, helps uncover unknown causes of cancer mutational signatures by analyzing associations. This method identified a link between Signature 17 and APOBEC activity in gastrointestinal cancers.

Keywords:
Excess zerosMutational signatureRosenblatt-Parzen kernel estimatorTest of independence

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Area of Science:

  • Genomics
  • Cancer Biology
  • Statistical Genetics

Background:

  • Cancers develop from somatic mutations, characterized by mutational signatures.
  • Unknown mutational processes hinder cancer prevention strategies.
  • Existing statistical tests lack power for analyzing mutational signatures due to excess zeros.

Purpose of the Study:

  • To develop a statistically powerful method for inferring the etiology of unknown mutational signatures.
  • To address the limitations of existing association tests in handling zero-inflated data.

Main Methods:

  • Proposed a semiparametric kernel independence test (SKIT) using integrated squared distance.
  • Decomposed the SKIT statistic to identify sources of dependency.
  • Utilized a bootstrap method for p-value computation due to slow asymptotic null distribution convergence.
  • Applied SKIT to The Cancer Genome Atlas (TCGA) data.

Main Results:

  • SKIT demonstrates resilience to power loss and robustness to errors in zero-prevalent data.
  • A novel association was found between Signature 17 and apolipoprotein B mRNA editing enzyme (APOBEC) signatures in gastrointestinal cancers.
  • This suggests APOBEC activity is linked to the etiology of Signature 17.

Conclusions:

  • SKIT is a powerful tool for uncovering the causes of unknown mutational signatures.
  • The findings suggest a role for APOBEC activity in the development of Signature 17 in gastrointestinal cancers.
  • This research aids in understanding cancer mutation processes and identifying potential interventions.