Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Long read alignment based on maximal exact match seeds.

Yongchao Liu1, Bertil Schmidt

  • 1Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz 55099, Germany. liuy@uni-mainz.de

Bioinformatics (Oxford, England)
|September 11, 2012
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Association of GPX4 rs713041 and rs4807542 polymorphisms and serum GPX4 levels in Chinese patients with systemic lupus erythematosus.

Lupus·2026
Same author

EGR1 Mediates Ursodeoxycholic Acid-Promoted Mitophagy to Prevent Postovulatory Aging of Porcine Oocytes.

Aging cell·2026
Same author

Optimizing snake fang-inspired microneedles for transdermal liquid drug delivery.

Drug delivery and translational research·2026
Same author

Integrative analysis of gastric tissue transcriptomes and gastric cancer GWAS implicates candidate susceptibility genes.

American journal of human genetics·2026
Same author

Metabolic Reprogramming-Driven Cardiovascular Immune Damage: From Glyco-Lipotoxicity and Epigenetic Memory to Multidimensional Cross-Organ Communication Networks.

International journal of molecular sciences·2026
Same author

Lipid Metabolism Reprogramming in the Aging Brain: Glial-Mediated Pathogenic Mechanisms and Translational Strategies in Neurodegeneration.

International journal of molecular sciences·2026
Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026
Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
Same journal

EDEL: Enhancing Dense Retrievers for Curation of Biomedical Knowledge Bases.

Bioinformatics (Oxford, England)·2026
See all related articles

CUSHAW2 is a new, efficient long read aligner that offers high accuracy and speed for next-generation sequencing data. It performs well in read mapping quality and parallel scalability, outperforming other aligners.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Next-generation sequencing (NGS) generates massive datasets, challenging existing genome alignment tools.
  • Increasing read lengths from high-throughput sequencing technologies exacerbate inefficiencies in current aligners.

Purpose of the Study:

  • To introduce CUSHAW2, a novel aligner designed for efficient and accurate long read alignment.
  • To evaluate CUSHAW2's performance against established long read aligners.

Main Methods:

  • CUSHAW2 employs a parallelized seed-and-extend approach using maximal exact matches for gapped alignments.
  • Performance was assessed using simulated and real human genome datasets, comparing against BWA-SW, Bowtie2, and GASSST.

Main Results:

Related Experiment Videos

  • CUSHAW2 demonstrates superior alignment quality for both single-end and paired-end reads.
  • The aligner exhibits highly competitive execution speed and excellent parallel scalability with increasing CPU threads.

Conclusions:

  • CUSHAW2 is an accurate, memory-efficient, and fast long read aligner suitable for large-scale genomics.
  • Its parallel design makes it a valuable tool for handling growing NGS datasets.