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FracFixR: a compositional statistical framework for absolute proportion estimation between fractions in RNA

Alice Cleynen1,2, Agin Ravindran3, Nikolay Shirokikh1,4

  • 1Institut Montpelliérain Alexander Grothendieck (IMAG), University of Montpellier, Centre National de la Recherche Scientifique (CNRS), Montpellier, Occitanie, 34090, France.

Bioinformatics (Oxford, England)
|November 20, 2025
PubMed
Summary

FracFixR is a new statistical framework that accurately reconstructs RNA fraction proportions from RNA-seq data. This method corrects biases in RNA localization and translation studies, enabling more reliable comparisons between biological samples.

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • RNA sequencing (RNA-seq) is crucial for studying RNA dynamics.
  • Fractionated RNA-seq data interpretation faces compositional challenges.
  • Existing methods struggle with bias and lost RNA fractions.

Purpose of the Study:

  • To develop a statistical framework for accurate RNA fraction proportion reconstruction.
  • To address compositional biases in fractionated RNA-seq data.
  • To enable robust comparisons of RNA profiles across biological conditions.

Main Methods:

  • Developed FracFixR, a statistical framework using non-negative linear regression.
  • Models compositional relationships between whole and fractionated RNA samples.
  • Includes differential proportion testing using binomial GLM, logit, or beta-binomial models.

Main Results:

  • FracFixR accurately reconstructs fraction weights (Pearson correlation > 0.85).
  • The framework quantifies unrecoverable RNA material.
  • Enabled detection of differentially translated transcripts between cancer subtypes.

Conclusions:

  • FracFixR overcomes compositional challenges in fractionated RNA-seq data.
  • The framework improves the reliability of RNA localization and translation studies.
  • FracFixR enhances the utility of RNA-seq for comparative analyses.