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Related Experiment Video

Updated: Sep 20, 2025

Characterizing Mutational Load and Clonal Composition of Human Blood
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Estimating intraclonal heterogeneity and subpopulation changes from bulk expression profiles in CMap.

Chiao-Yu Hsieh1, Ching-Chih Tu1, Jui-Hung Hung2

  • 1Department of Computer Science, College of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.

Life Science Alliance
|June 10, 2022
PubMed
Summary

This study introduces Premnas, a computational framework to analyze cell subpopulation changes from bulk expression data. This approach enhances understanding of drug responses and biological pathways by addressing limitations of previous methods.

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Area of Science:

  • Computational Biology
  • Genomics
  • Systems Biology

Background:

  • The Connectivity Map (CMap) library offers insights into drug and disease pathways through perturbation signatures.
  • Bulk expression profiling (L1000 assay) in CMap overlooks intraclonal heterogeneity and subpopulation dynamics, limiting interpretability.
  • Understanding subpopulation shifts is crucial for deciphering cellular responses to perturbations.

Purpose of the Study:

  • To develop a computational framework, Premnas, for estimating subpopulation abundance from L1000 profiles.
  • To leverage archetypal analysis on single-cell RNA-seq data to represent cell subpopulations.
  • To explore drug-resistant/susceptible subpopulations within CMap L1000 data.

Main Methods:

  • Archetypal analysis applied to single-cell RNA-seq datasets to define subpopulation representations.
  • Development of the Premnas computational framework to estimate subpopulation abundance from bulk L1000 expression profiles.
  • Analysis of CMap L1000 data to recover and examine subpopulation changes upon perturbation.

Main Results:

  • Premnas successfully estimates subpopulation abundance from L1000 profiles, recovering previously neglected information.
  • The framework facilitates the exploration of drug-resistant and susceptible subpopulations.
  • New insights into the connectivity of cellular signatures are gained by accounting for subpopulation dynamics.

Conclusions:

  • Premnas offers a novel computational approach to overcome the limitations of bulk profiling in perturbation datasets like CMap.
  • The framework enhances the interpretability and reproducibility of biological insights derived from perturbation studies.
  • This work expands the utility of CMap and similar datasets by incorporating subpopulation-level analysis.