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Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.

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.
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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...

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Updated: May 17, 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

CD-HIT: accelerated for clustering the next-generation sequencing data.

Limin Fu¹, Beifang Niu, Zhengwei Zhu

¹Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.

Bioinformatics (Oxford, England)

|October 13, 2012

Summary

This summary is machine-generated.

A new version of CD-HIT (commonly used for clustering biological sequences) has been developed to handle massive next-generation sequencing data. This enhanced CD-HIT program offers significant speedups, enabling faster analysis of large biological datasets.

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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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Introductory Analysis and Validation of CUT&RUN Sequencing Data

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Published on: December 13, 2024

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

CD-HIT is a standard tool for reducing redundancy in biological sequence datasets.
Next-generation sequencing technologies generate vast amounts of data, necessitating efficient analysis tools.

Purpose of the Study:

To develop an accelerated version of CD-HIT capable of handling large-scale sequencing data.
To improve the efficiency and speed of biological sequence clustering.

Main Methods:

Implementation of a novel parallelization strategy within the CD-HIT program.
Incorporation of additional optimization techniques for enhanced performance.

Main Results:

Demonstrated significant speedup with parallelization, achieving quasi-linear speedup up to ~8 cores and good speedup up to ~24 cores.
The enhanced CD-HIT effectively handles very large datasets in reduced time compared to previous versions.

Conclusions:

The developed CD-HIT program is highly efficient for clustering massive biological sequence datasets.
This enhancement addresses the challenges posed by the increasing volume of sequencing data, improving downstream analyses.