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DifferentialRegulation: a Bayesian hierarchical approach to identify differentially regulated genes.

Simone Tiberi1,2, Joël Meili2, Peiying Cai2

  • 1Department of Statistical Sciences, University of Bologna, Via delle Belle Arti 41, Bologna, 40126, Italy.

Biostatistics (Oxford, England)
|June 18, 2024
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Summary

This study introduces DifferentialRegulation, a new Bayesian method for comparing spliced and unspliced mRNA levels between sample groups. It addresses quantification uncertainty to accurately detect gene expression changes in bulk and single-cell RNA sequencing data.

Keywords:
Bayesian hierarchical modelBayesian inferenceRNA-sequencing databioinformaticslatent variablesstatistical software tooltranscriptomics

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Transcriptomics typically analyzes mature spliced mRNA.
  • Investigating both spliced and unspliced (precursor) mRNA offers insights into gene regulation and expression dynamics.
  • Current methods for spliced/unspliced inference often lack group comparison capabilities and struggle with quantification uncertainty.

Purpose of the Study:

  • To develop a robust method for comparing spliced and unspliced mRNA abundance between experimental conditions.
  • To address and model the high degree of quantification uncertainty inherent in spliced/unspliced mRNA data.
  • To provide a flexible tool applicable to both bulk and single-cell RNA sequencing.

Main Methods:

  • Developed DifferentialRegulation, a Bayesian hierarchical model.
  • Employed a latent variable approach to model quantification uncertainty by allocating reads to their gene/transcript and splice version.
  • Designed benchmarks to evaluate performance against existing methods.

Main Results:

  • DifferentialRegulation demonstrates strong performance in sensitivity and error control in benchmark tests.
  • The method effectively handles quantification uncertainty arising from multi-mapping reads.
  • The tool is validated for use with both bulk and single-cell RNA sequencing data.

Conclusions:

  • DifferentialRegulation provides a powerful new approach for differential analysis of spliced and unspliced mRNA.
  • The method enhances the ability to study gene regulation and expression changes across different experimental conditions.
  • The Bioconductor R package offers a flexible and accurate solution for the research community.