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Updated: Mar 16, 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

fluff: exploratory analysis and visualization of high-throughput sequencing data.

Georgios Georgiou¹, Simon J van Heeringen¹

¹Radboud University, Molecular Developmental Biology , Nijmegen , The Netherlands.

|August 23, 2016

Summary

This summary is machine-generated.

Fluff is a new software package for easy exploration, clustering, and visualization of high-throughput sequencing data. It provides command-line tools to generate publication-quality figures and integrate into analysis pipelines.

Keywords:

ChIP-seq Clustering High-throughput sequencing Next-generation sequencing Python Visualization

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

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Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

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Published on: June 28, 2018

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

High-throughput sequencing generates large datasets requiring efficient analysis tools.
Visualizing and clustering genomic data is crucial for understanding biological patterns.

Purpose of the Study:

To introduce fluff, a software package for simplified exploration, clustering, and visualization of high-throughput sequencing data.
To provide command-line tools for generating publication-quality figures from genomic data.

Main Methods:

The fluff package offers three command-line tools for data aggregation, clustering, and visualization.
Supports heatmap and bandplot visualizations with various clustering methods.
Includes a tool for generating genomic profiles.

Main Results:

Fluff enables straightforward aggregation, clustering, and visualization of genome-wide sequencing data.
Facilitates identification of dynamic clusters across different conditions or developmental stages.
Generates publication-quality figures with sensible defaults.

Conclusions:

Fluff is a user-friendly software package for analyzing high-throughput sequencing data.
Its command-line nature allows seamless integration into existing bioinformatics pipelines.
The package is implemented in Python, runs on Linux, and is freely available.