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Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

Published on: January 19, 2017

Marker gene fishing for single-cell data with complex heterogeneity.

Yiren Shao, Qi Gao, Liuyang Wang

Biorxiv : the Preprint Server for Biology

|November 22, 2024

Summary

B-Lightning is a new method that identifies key cell markers and subpopulations by filtering out irrelevant biological variations. This robust tool enhances single-cell data analysis, improving the accuracy of identifying cell states like activation or senescence.

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Single Cell Analysis Of Transcriptionally Active Alleles By Single Molecule FISH

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Published on: September 20, 2020

Area of Science:

Computational Biology
Genomics
Immunology

Background:

Single-cell studies involve complex data with multiple sources of heterogeneity.
Nuisance sources of heterogeneity (SOH) can obscure the identification of biologically relevant SOH.
Accurate annotation of cell subpopulations is crucial for understanding cellular states.

Purpose of the Study:

To develop a novel and robust method, B-Lightning, for identifying marker genes and cell subpopulations related to a specific SOH.
To isolate the SOH of interest from other confounding factors like cell type or cell cycle phase.
To improve the sensitivity and robustness of marker gene identification in single-cell analysis.

Main Methods:

B-Lightning employs an iterative approach to refine marker genes.
It enriches trustworthy marker genes to boost signals of the SOH of interest.
The method is validated through numerical simulations and experimental studies.

Main Results:

B-Lightning outperforms existing methods in identifying marker genes with increased sensitivity and robustness.
It enhances the ability to differentiate cell subpopulations of interest.
New senescence markers in lung tissues and T cell markers in SARS-CoV-2 infections were identified.

Conclusions:

B-Lightning is a powerful tool for single-cell data analysis, especially in complex datasets.
It effectively isolates and identifies specific sources of heterogeneity.
The method has demonstrated success in identifying novel biological markers and patterns previously overlooked.