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OASIS: An interpretable, finite-sample valid alternative to Pearson's for scientific discovery.

Tavor Z Baharav1, David Tse1, Julia Salzman2,3,4

  • 1Department of Electrical Engineering, Stanford University, Stanford, CA 94305.

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|November 14, 2023
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Summary
This summary is machine-generated.

A new statistical test, Optimized Adaptive Statistic for Inferring Structure (OASIS), offers efficient and valid analysis for contingency tables. It outperforms existing methods in genomic applications, detecting pathogens and improving false discovery rate control.

Keywords:
Alignment-free inferenceComputational genomicsContingency tableFinite-sample p-value bound

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Area of Science:

  • Statistics
  • Genomics
  • Computational Biology

Background:

  • Contingency tables are widely used in quantitative research but existing statistical tests lack computational efficiency and statistical validity for finite samples.
  • Reference-free genomic inference presents a specific challenge requiring novel statistical approaches for analyzing count data.

Approach:

  • Developed OASIS (Optimized Adaptive Statistic for Inferring Structure), a novel family of statistical tests for contingency tables.
  • Constructed a test statistic linear in the normalized data matrix, enabling closed-form p-value bounds via concentration inequalities.
  • Derived the asymptotic distribution of the OASIS test statistic, validating finite-sample bounds and providing interpretability through table decomposition.

Key Points:

  • OASIS demonstrates significant power and interpretability in genomic sequencing data analysis.
  • The method successfully detects SARS-CoV-2 and Mycobacterium Tuberculosis strains de novo, surpassing current approaches.
  • OASIS exhibits robustness to overdispersion common in genomic data, maintaining false discovery rate control where Pearson's chi-squared test fails.

Conclusions:

  • OASIS provides a computationally efficient and statistically valid alternative for contingency table analysis.
  • Its applications in genomics highlight its potential for novel pathogen detection and robust data analysis.
  • OASIS offers superior power in specific scenarios compared to traditional methods like Pearson's chi-squared test.