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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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Updated: Sep 11, 2025

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

Single-cell sequencing: accurate disease detection.

XiaoQin Wang¹, NianNian Li¹, Wei Wang²

¹Weifang People's Hospital, Weifang, China.

Clinical & Translational Oncology : Official Publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico

|August 16, 2025

Summary

This summary is machine-generated.

Single-cell sequencing offers new ways to detect diseases early by analyzing individual cell differences. This technology promises to revolutionize clinical diagnosis despite current challenges.

Keywords:

Accurate disease detection Single-cell sequencing Tumor

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Last Updated: Sep 11, 2025

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Area of Science:

Genomics
Molecular Biology
Biotechnology

Background:

Early disease detection significantly improves treatment outcomes and patient prognosis.
Traditional sequencing methods have limitations in capturing cellular heterogeneity.
Single-cell sequencing technology provides a novel approach to analyze biological samples.

Purpose of the Study:

To explore the potential of single-cell sequencing for early and accurate disease detection.
To highlight the application of single-cell sequencing in understanding neurological diseases.
To discuss the advantages and challenges of implementing single-cell sequencing in clinical settings.

Main Methods:

Analysis of genomic and transcriptomic data at the single-cell level.
Demonstration of cellular heterogeneity through single-cell analysis.
Application of single-cell sequencing to identify early-stage gene expression changes in neurological diseases.

Main Results:

Single-cell sequencing reveals cellular heterogeneity, which is crucial for understanding disease mechanisms.
The technology can detect early-stage gene expression alterations in nerve cells, aiding in early diagnosis.
Single-cell sequencing facilitates disease monitoring by providing detailed cellular insights.

Conclusions:

Single-cell sequencing holds significant promise for accurate disease detection and monitoring.
Despite challenges like complex data processing and high costs, technological advancements are expected.
This technology is poised to revolutionize clinical diagnosis and patient care.