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Updated: Jun 5, 2026

Transcriptome Analysis of Single Cells

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

Methods toward Single-Cell Total-Analysis.

Qiang Zhang^1,2, Wenjun Liao³, Ling Lin³

¹Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Beijing Key Laboratory of Microanalysis Methods and Instrumentation, Department of Chemistry, Tsinghua University, Beijing 100084, China.

Chemical Reviews

|June 3, 2026

Summary

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This summary is machine-generated.

Single-cell total-analysis aims to link molecular data with cell function. True analysis requires direct phenotype-component correlation, not just accumulating molecular layers.

Area of Science:

Single-cell biology
Systems biology
Omics technologies

Background:

Single-cell analysis seeks to connect molecular profiles (genomics, transcriptomics, proteomics, metabolomics) with cellular function.
Current omics technologies are mature for nucleic acids but incomplete for proteins/metabolites, hindering comprehensive phenomics.
A significant challenge is correlating molecular data with direct functional phenotypes within individual cells.

Purpose of the Study:

To review advances in single-cell omics and multiomics integration.
To identify bottlenecks hindering comprehensive single-cell total-analysis.
To propose a roadmap for unifying molecular and phenotypic landscapes in single cells.

Main Methods:

Examination of advances across five core omics domains.

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Integrated Cell Manipulation Platform Coupled with the Single-probe for Mass Spectrometry Analysis of Drugs and Metabolites in Single Suspension Cells

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Transcriptome Analysis of Single Cells

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Analysis of bottlenecks in current single-cell multiomics approaches.

Review of multiomics co-analysis strategies and their limitations.

Main Results:

Nucleic acid-based omics are advanced, but proteomic, metabolomic, and phenomic data remain incomplete.
Multimodal integration faces technical, throughput, and temporal resolution challenges.
Existing multiomics approaches often fail to establish direct molecular-phenotypic correlations.

Conclusions:

True single-cell total-analysis requires direct correlation of phenotype with molecular components.
Accumulating multiple molecular layers alone does not constitute comprehensive single-cell analysis.
Future research should focus on breakthrough approaches to unify molecular and phenotypic data within single cells.