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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.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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...

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Related Experiment Video

Updated: Mar 8, 2026

Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

A fast read alignment method based on seed-and-vote for next generation sequencing.

Song Liu^1,2, Yi Wang³, Fei Wang^4,5

¹Shanghai Key Lab of Intelligent Information Processing, Shanghai, China.

BMC Bioinformatics

|February 4, 2017

Summary

This summary is machine-generated.

A new read alignment tool, Fast Seed-and-Vote Aligner (FSVA), offers high accuracy comparable to BWA but is 5-7 times faster. FSVA significantly improves whole genome read alignment speed for bioinformatics research.

Keywords:

Hash table Read alignment Seed and vote

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Area of Science:

Bioinformatics
Genomics
Computational Biology

Background:

Next-generation sequencing generates vast amounts of data daily.
Efficient read alignment to reference genomes is crucial for downstream bioinformatics analysis.
Existing read alignment tools often present a trade-off between accuracy and speed, with tools like BWA being accurate but slow.

Purpose of the Study:

To develop a novel read alignment tool that balances high accuracy with significantly improved speed.
To address the bottleneck in processing large volumes of sequencing reads.
To provide a faster alternative for whole genome read alignment.

Main Methods:

Implementation of a new read alignment tool named Fast Seed-and-Vote Aligner (FSVA).
The FSVA tool is based on the seeding and voting algorithm.
Evaluation of FSVA's performance in terms of accuracy and speed compared to existing tools.

Main Results:

FSVA achieves high accuracy, comparable to the BWA aligner.
FSVA demonstrates a substantially higher speed, being approximately 5-7 times faster than BWA.
Whole genome read alignment using FSVA requires only ~10-15 CPU hours.

Conclusions:

FSVA presents a promising option for read alignment when speed is a critical factor and stringent accuracy is not paramount.
The tool offers a significant speed improvement for bioinformatics workflows.
FSVA is publicly available for use and further development.