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

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.

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...

You might also read

Related Articles

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

Sort by

Same author

<i>Pfcrt</i> copy number amplification detected in a <i>Plasmodium falciparum</i> outbreak.

bioRxiv : the preprint server for biology·2026

Same author

Associations between the Plasmodium falciparum genome and sickle haemoglobin identified in mild malaria cases from Ghana.

Malaria journal·2026

Same author

Major features of parasite adaptation revealed by genomes of Plasmodium falciparum population samples archived for over 50 years.

Communications biology·2026

Same author

Pf8: an open dataset of <i>Plasmodium falciparum </i>genome variation in 33,325 worldwide samples.

Wellcome open research·2025

Same author

Microhaplotype deep sequencing assays to capture Plasmodium vivax infection lineages.

Nature communications·2025

Same author

Identification of complex Plasmodium falciparum genetic backgrounds circulating in Africa: a multicountry genomic epidemiology analysis.

The Lancet. Microbe·2024

Search research articles

Related Experiment Video

Updated: Jun 21, 2026

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

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

Published on: June 28, 2018

LookSeq: a browser-based viewer for deep sequencing data.

Heinrich Magnus Manske¹, Dominic P Kwiatkowski

¹Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, United Kingdom. mm6@sanger.ac.uk

Genome Research

|August 15, 2009

Summary

This summary is machine-generated.

Deep sequencing reveals genomic heterogeneity. The LookSeq web viewer offers interactive visualization of complex sequence data, aiding in the detection of structural variations and sample heterogeneity.

More Related Videos

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

Related Experiment Videos

Last Updated: Jun 21, 2026

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

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

Published on: June 28, 2018

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Deep genome sequencing provides rich data on individual and population heterogeneity.
Visualizing complex, multi-layered deep sequencing data presents significant challenges.

Purpose of the Study:

To develop an effective method for visualizing deep sequencing data.
To facilitate the assimilation of information at various resolutions, from genomic overviews to fine-scale heterogeneity.
To improve the depiction of structural variations in heterogeneous samples.

Main Methods:

Development of an interactive AJAX-based web viewer named LookSeq.
Implementation of seamless browsing and fast zooming capabilities.
Graphical representation of paired sequence reads for structural variation analysis.

Main Results:

LookSeq enables efficient browsing and zooming of large aligned sequence read datasets.
The viewer facilitates understanding of genomic heterogeneity at multiple resolutions.
LookSeq offers improved graphical representation for detecting insertions and deletions compared to conventional methods.

Conclusions:

LookSeq is an effective tool for visualizing complex deep sequencing data.
The program aids researchers in identifying genomic heterogeneity and structural variations.
Interactive visualization enhances the interpretation of deep sequencing results.