Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Sanger Sequencing

Sanger Sequencing

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...

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 microarray-based...

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.

Maxam-Gilbert Sequencing

Maxam-Gilbert Sequencing

In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

Cell genomics·2022

Same author

CRAM 3.1: advances in the CRAM file format.

Bioinformatics (Oxford, England)·2022

Same author

HTSlib: C library for reading/writing high-throughput sequencing data.

GigaScience·2021

Same author

Twelve years of SAMtools and BCFtools.

GigaScience·2021

Same author

Crumble: reference free lossy compression of sequence quality values.

Bioinformatics (Oxford, England)·2018

Same author

De novo yeast genome assemblies from MinION, PacBio and MiSeq platforms.

Scientific reports·2017

Search research articles

Related Experiment Video

Updated: May 12, 2026

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Compression of FASTQ and SAM format sequencing data.

James K Bonfield¹, Matthew V Mahoney

¹Wellcome Trust Sanger Institute, Cambridge, United Kingdom. jkb@sanger.ac.uk

|March 28, 2013

Summary

New compression tools, Fastqz and Samcomp/Fqzcomp, offer state-of-the-art data compression ratios for FASTQ files from DNA sequencing at affordable computational costs.

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Modern DNA sequencing generates massive datasets, posing significant storage and transmission challenges.
The Pistoia Alliance initiated the SequenceSqueeze contest to address the need for efficient FASTQ file compression.

Purpose of the Study:

To evaluate and present novel compression algorithms for FASTQ files.
To compare the performance of new tools against existing reference-based and non-reference-based compression methods.

Main Methods:

The study presents Fastqz and Samcomp/Fqzcomp, including the winning SequenceSqueeze contest entry.
Performance was benchmarked against established algorithms like CRAM, Goby, DSRC, BAM, Quip, and SCALCE.

Main Results:

Related Experiment Videos

Last Updated: May 12, 2026

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Fastqz and Samcomp/Fqzcomp establish a new Pareto frontier for FASTQ compression.
These tools achieve state-of-the-art compression ratios with efficient CPU usage.

Conclusions:

The presented tools offer a significant advancement in FASTQ data compression efficiency.
All evaluated programs are freely available, promoting wider adoption in genomic data management.