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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: Dec 25, 2025

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

Methods for ChIP-seq analysis: A practical workflow and advanced applications.

Ryuichiro Nakato¹, Toyonori Sakata²

¹Laboratory of Computational Genomics, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan.

Methods (San Diego, Calif.)

|April 3, 2020

Summary

This summary is machine-generated.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a key epigenomic method. This review covers practical ChIP-seq analysis, advanced applications like predicting gene expression, and single-cell methods for tissue and cancer research.

Keywords:

ChIP-seq Chromatin state Histone modifications Machine learning Quality assessment Single-cell analysis

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Last Updated: Dec 25, 2025

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

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Published on: June 8, 2020

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Area of Science:

Epigenomics
Molecular Biology
Genomics

Background:

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a fundamental technique in epigenomic research.
It enables genome-wide analysis of histone modifications, crucial for understanding cell identity, development, and disease.
Epigenomic landscape analysis is vital for systematic studies in biological systems.

Purpose of the Study:

To provide a practical overview of the ChIP-seq analysis workflow.
To introduce advanced ChIP-seq applications and state-of-the-art methodologies.
To discuss emerging single-cell ChIP-seq techniques for cellular diversity analysis.

Main Methods:

Detailed presentation of a typical ChIP-seq analysis workflow, including quality assessment and chromatin-state annotation.
Outline of advanced ChIP-seq applications such as enhancer analysis and chromatin loop prediction.
Introduction to data imputation and single-cell ChIP-seq analysis methodologies.

Main Results:

The review focuses on practical approaches for biological studies using ChIP-seq.
Advanced methods for predicting gene expression and chromatin loops from epigenome data are presented.
Single-cell ChIP-seq methodologies are discussed for elucidating cellular heterogeneity.

Conclusions:

ChIP-seq is a versatile tool for dissecting the epigenomic landscape.
Advanced and single-cell ChIP-seq methods offer powerful insights into complex biological systems and diseases.
This review serves as a practical guide for researchers utilizing ChIP-seq in their studies.