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Related Experiment Video

Updated: May 27, 2025

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Fast, flexible analysis of differences in cellular composition with crumblr.

Gabriel E Hoffman1,2,3,4,5,6, Panos Roussos1,2,3,4,5,6

  • 1Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Biorxiv : the Preprint Server for Biology
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PubMed
Summary

We developed crumblr, a new statistical method to analyze cell type composition changes in large datasets. This method enhances the power to detect cell type frequency shifts in complex diseases and biological studies.

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Area of Science:

  • Genomics
  • Computational Biology
  • Biostatistics

Background:

  • Cell type composition is crucial in human health and disease.
  • Single-cell technologies provide high-resolution cell lineage data but pose analytical challenges.
  • Identifying changes in cell type frequency requires robust statistical methods.

Purpose of the Study:

  • To introduce crumblr, a scalable statistical method for analyzing cell type compositional data.
  • To enable precise statistical testing at multiple levels of the cell lineage hierarchy.
  • To improve power and control false positive rates in compositional data analysis.

Main Methods:

  • Developed crumblr, a method using precision-weighted linear mixed models.
  • Incorporated random effects to accommodate complex study designs.
  • Utilized a multivariate approach for statistical testing across cell lineage hierarchies.

Main Results:

  • Simulations show crumblr increases statistical power compared to existing methods.
  • crumblr effectively controls the false positive rate.
  • Demonstrated application on diverse single-cell RNA-seq datasets (aging, tuberculosis, prostate cancer, SARS-CoV-2).

Conclusions:

  • crumblr offers a powerful and scalable solution for analyzing cell type composition in large-scale single-cell studies.
  • The method is applicable to various biological contexts, including disease and aging.
  • Facilitates deeper insights into the role of cell type dynamics in health and disease.