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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: Mar 18, 2026

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

Published on: October 5, 2018

w4CSeq: software and web application to analyze 4C-seq data.

Mingyang Cai¹, Fan Gao², Wange Lu³

¹Department of Preventive Medicine Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research Zilkha Neurogenetic Institute.

Bioinformatics (Oxford, England)

|July 6, 2016

Summary

This summary is machine-generated.

We developed w4CSeq, a user-friendly computational tool for analyzing Circularized Chromosome Conformation Capture sequencing (4C-Seq) data. This software identifies genome-wide interacting regions and visualizes their genomic context.

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High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

Published on: October 5, 2018

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Area of Science:

Genomics
Computational Biology
Molecular Biology

Background:

Circularized Chromosome Conformation Capture followed by deep sequencing (4C-Seq) is a key method for identifying long-range genomic interactions.
Analyzing 4C-Seq data, especially from diverse fragmentation methods, presents computational challenges.

Purpose of the Study:

To present a robust computational and statistical approach for analyzing 4C-Seq data.
To introduce w4CSeq, a software tool and web interface for user-friendly 4C-Seq data analysis.

Main Methods:

Development of a command-line software tool and a web interface (w4CSeq).
Implementation of automated statistical analysis for raw 4C-Seq data (FASTQ files).
Integration of visualization of interacting regions and enrichment analysis of genomic features (TSSs, TTSs, CpG sites, replication timing).

Main Results:

w4CSeq successfully analyzes 4C-Seq data from both enzyme digestion and sonication methods.
The tool provides lists of candidate interacting sites/regions.
Genome-wide distribution and feature enrichment around interacting regions are visualized.

Conclusions:

w4CSeq offers an accessible and automated solution for 4C-Seq data analysis.
The tool facilitates the identification and characterization of 3D genome organization.
w4CSeq supports researchers in understanding genome-wide interactions and their functional context.