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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...

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Updated: Mar 2, 2026

Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Short Read Mapping: An Algorithmic Tour.

Stefan Canzar, Steven L Salzberg

Proceedings of the IEEE. Institute of Electrical and Electronics Engineers

|May 16, 2017

Summary

This summary is machine-generated.

Next-generation sequencing (NGS) generates massive DNA sequence data. Efficient algorithms are crucial for mapping these short reads to a reference genome, enabling biological discoveries.

Keywords:

Burrows-Wheeler transform DNA sequencing sequence alignment string matching suffix trees

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Next-generation sequencing (NGS) technology enables parallel sequencing of millions of DNA molecules.
NGS has significantly reduced costs since 2004, revolutionizing biological and biomedical research.
NGS data consists of numerous short DNA sequences ('reads') requiring complex analysis.

Purpose of the Study:

To address the challenge of analyzing vast amounts of short DNA sequence data generated by NGS.
To explain the necessity of mapping NGS reads to a reference genome for biological interpretation.
To highlight the development of efficient algorithms for handling NGS data alignment.

Main Methods:

Utilizing ultra-high-throughput next-generation sequencing (NGS) technology.
Employing well-engineered algorithms for piecing together short DNA sequences (reads).
Developing and applying efficient read mapping algorithms tolerant of mismatches, insertions, and deletions.

Main Results:

NGS technology provides a powerful approach for diverse biological and biomedical questions.
Mapping short reads to a reference genome is essential for reconstructing biological measurements.
Efficient alignment algorithms are critical for analyzing hundreds of millions of reads against large genomes like the human genome.

Conclusions:

NGS technology has transformed biological research by enabling large-scale DNA sequencing.
Sophisticated bioinformatics algorithms are indispensable for accurate analysis of NGS data.
The development of efficient read mapping methods is key to the routine global analysis of NGS data.