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Updated: Mar 18, 2026
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Targeted DNA Methylation Analysis by Next-generation Sequencing
Published on: February 24, 2015
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A Survey of Software and Hardware Approaches to Performing Read Alignment in Next Generation Sequencing
Summary
Computational genomics uses Next Generation Sequencing (NGS) data for biological discovery. This paper surveys NGS read alignment algorithms and hardware acceleration, highlighting overlooked biological features in current approaches.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Next Generation Sequencing (NGS) generates vast amounts of genomic data.
- Read alignment is crucial for mapping NGS sequences to a reference genome.
- Existing alignment algorithms face challenges with space and time complexity.
Purpose of the Study:
- To introduce computational genomics and NGS technologies.
- To discuss popular NGS read alignment tools and algorithms.
- To survey hardware implementations for accelerating read alignment.
Main Methods:
- Review of computational genomics principles.
- Analysis of Next Generation Sequencing data processing.
- Survey of existing read alignment algorithms and hardware acceleration techniques.
Main Results:
- Identification of key read alignment algorithms and their computational demands.
- Overview of various hardware acceleration strategies for read alignment.
- Highlighting limitations of current hardware approaches in addressing biological features.
Conclusions:
- Read alignment is a critical step in genomic data analysis.
- Hardware acceleration offers significant speedups but often compromises biological accuracy.
- Further development is needed to integrate biological features into hardware-accelerated alignment methods for wider adoption.
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