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RNA-seq

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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.
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Related Experiment Video

Updated: Jul 9, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Practical Compass of Single-Cell RNA-Seq Analysis.

Hiroyuki Okada^1,2,3, Ung-Il Chung^4,5, Hironori Hojo^4,5

¹Center for Disease Biology and Integrative Medicine, Graduate School of Medicine, The University of Tokyo, Bunkyo-Ku, Tokyo, 113-8655, Japan. hokada-tky@g.ecc.u-tokyo.ac.jp.

Current Osteoporosis Reports

|November 29, 2023

Summary

This summary is machine-generated.

This review guides researchers through single-cell RNA sequencing (scRNA-seq) data analysis, from handling datasets to visualizing results. It highlights scRNA-seq applications in skeletal biology and the need for improved analytical tools.

Keywords:

Computational analysis Dry analysis Practical compass Single cell RNA-seq Transcriptome

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Last Updated: Jul 9, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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

Transcriptome Analysis of Single Cells

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

Area of Science:

Genomics
Bioinformatics
Cell Biology

Background:

Single-cell RNA sequencing (scRNA-seq) is increasingly used to study cellular heterogeneity and interactions.
Applications in skeletal biology include osteoclast differentiation, fracture healing, and bone development.
Development of user-friendly packages for ligand-receptor and trajectory analyses is ongoing.

Purpose of the Study:

To provide step-by-step instructions for fundamental scRNA-seq data analysis.
To offer a guide for complex analytical processes in scRNA-seq.
To address the need for updated information and knowledge sharing in scRNA-seq analysis.

Main Methods:

Review of fundamental processes in scRNA-seq data handling.
Explanation of methods for illustrating plots and drawing trajectories.
Discussion of available user-friendly scRNA-seq packages.

Main Results:

scRNA-seq reveals cellular heterogeneity and cell type interactions.
Numerous skeletal biology processes have been examined using scRNA-seq.
Tools for scRNA-seq data analysis, including dataset integration, are still under development.

Conclusions:

Researchers need to share knowledge for better biological interpretation of scRNA-seq data.
This review serves as a valuable guide for complex scRNA-seq analytical processes.
Continued development of analytical tools is crucial for advancing scRNA-seq research.