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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Related Experiment Video

Updated: Jun 27, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

CPPLS-MLP: a method for constructing cell-cell communication networks and identifying related highly variable genes

Tianjiao Zhang¹, Zhenao Wu¹, Liangyu Li¹

¹College of Computer and Control Engineering, Northeast Forestry University Harbin, 150040, China.

Briefings in Bioinformatics

|April 28, 2024

Summary

This summary is machine-generated.

CPPLS-MLP identifies highly variable genes (HVGs) linked to cell communication, improving cell communication network accuracy. This method analyzes how multiple communication pathways impact HVG expression, outperforming existing approaches.

Keywords:

ST-seq cell communication highly variable genes scRNA-seq

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Last Updated: Jun 27, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

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Published on: October 25, 2018

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Published on: January 10, 2019

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

Area of Science:

Cellular Biology
Genomics
Bioinformatics

Background:

Cell communication is vital for multicellular organism development and homeostasis.
Current methods often overlook the link between intercellular communication and highly variable genes (HVGs).
Advances in single-cell sequencing (scRNA-seq) and spatial transcriptomics enable new analyses of cell communication.

Purpose of the Study:

To develop a method for identifying HVGs associated with intercellular communication.
To analyze the influence of multiple input, multiple output (MIMO) cellular communication on HVG differential expression.
To enhance the accuracy of cell communication network construction.

Main Methods:

Proposed CPPLS-MLP method for identifying communication-related HVGs.
Utilized scRNA-seq and spatial transcriptomics data.
Compared CPPLS-MLP performance against the CCPLS method.

Main Results:

CPPLS-MLP effectively identifies cell-type-specific HVGs.
The method accurately analyzes the impact of neighboring cell types on HVG expression.
Demonstrated superior performance compared to CCPLS in network construction.

Conclusions:

CPPLS-MLP offers a robust approach for understanding HVG regulation by cell communication.
Accurate identification of communication-related HVGs refines cell communication network analysis.
The findings contribute to a deeper understanding of multicellular organism development and immune processes.