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

Fragment assembly with short reads.

Mark Chaisson1, Pavel Pevzner, Haixu Tang

  • 1Bioinformatics Program, University of California San Diego, La Jolla, CA 92093, USA. mchaisso@bioinf.ucsd.edu

Bioinformatics (Oxford, England)
|April 3, 2004
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

Cross-chemical and cross-species toxicity prediction: benchmarking and a novel 3D-structure-based deep learning model.

Environmental toxicology and chemistry·2026
Same author

AKI-twinX: explainable organ structured digital twin for sepsis AKI trajectory forecasting.

medRxiv : the preprint server for health sciences·2026
Same author

Comprehensive top-down mass spectral repository enables pan-dataset analysis and top-down spectral prediction.

bioRxiv : the preprint server for biology·2026
Same author

FIDDLE: a deep learning method for chemical formulas prediction from tandem mass spectra.

Nature communications·2025
Same author

Long-read sequencing identifies FGF14 repeat expansions in Parkinson's disease.

Brain : a journal of neurology·2025
Same author

Koina: Democratizing machine learning for proteomics research.

Nature communications·2025
Same journal

Cross-Domain Transfer Learning from Peptides to Metabolites Using a Multi-Property Fine-Tuned LLM.

Bioinformatics (Oxford, England)·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
See all related articles

New DNA sequencing technologies offer higher coverage with shorter reads. Assembling these short reads is feasible but may require extensive finishing efforts due to inherent limitations.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Current DNA sequencing technologies yield longer reads (500-750 bp) with low coverage (<10x).
  • Emerging sequencing technologies produce shorter reads (80-200 bp) at higher coverage (30x+) and lower cost.
  • Existing assembly programs are optimized for longer reads and may not perform optimally with short reads.

Purpose of the Study:

  • To analyze the limitations of assembling short DNA sequencing reads.
  • To present a novel routine for base-calling prior to assembly of short reads.
  • To evaluate the feasibility and downstream requirements for assembling short reads.

Main Methods:

  • Analysis of assembly limitations for short DNA reads.
  • Development and application of a pre-assembly base-calling routine.

Related Experiment Videos

  • Assessment of contig quality and finishing effort required for short-read assemblies.

    • Main Results:

    • Assembly of short reads is demonstrated to be feasible.
    • The resulting assembled contigs necessitate significant finishing efforts.
    • A base-calling routine is presented to improve short-read assembly.

    Conclusions:

    • Short-read sequencing technologies present unique challenges for genome assembly.
    • Pre-assembly base-calling can mitigate some issues but finishing remains a bottleneck.
    • Further development of assembly algorithms is needed for efficient short-read data utilization.