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 Video

Updated: May 11, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Specificity control for read alignments using an artificial reference genome-guided false discovery rate.

Sven H Giese1, Franziska Zickmann, Bernhard Y Renard

  • 1Research Group Bioinformatics (NG4), Robert Koch-Institut, Nordufer 20, 13353 Berlin, Germany.

Bioinformatics (Oxford, England)
|May 21, 2013
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

Selecting synthetic data for successful simulation-based transfer learning in dynamical biological systems.

BMC bioinformatics·2026
Same author

Molecular features of human pathological tau distinguish tauopathy-associated dementias.

Cell·2026
Same author

Automating clinical phenotyping using natural language processing.

Communications medicine·2026
Same author

Disease duration impacts intestinal gene expression profiles in Crohn's disease but not in ulcerative colitis.

Journal of Crohn's & colitis·2025
Same author

Distinct perturbances in metabolic pathways associate with disease progression in inflammatory bowel disease.

Journal of Crohn's & colitis·2025
Same author

End-to-end simulation of nanopore sequencing signals with feed-forward transformers.

Bioinformatics (Oxford, England)·2024
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

Accurate read mapping is vital for next-generation sequencing analysis. ARDEN (artificial reference driven estimation of false positives) is a novel method using real data to precisely quantify read mapping errors, improving downstream analysis.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Accurate read mapping is critical for next-generation sequencing (NGS) data analysis.
  • Existing methods for error rate estimation often focus on sensitivity or rely on potentially biased read simulations.
  • There is a need for methods that accurately assess mapping accuracy using real experimental data.

Purpose of the Study:

  • To introduce ARDEN (artificial reference driven estimation of false positives), a novel benchmark method for estimating read mapping error rates.
  • To provide a dataset-specific approach for quantifying mapping errors and constructing receiver operating characteristic curves.
  • To enable optimization of read mapper parameters, selection of appropriate mappers, and quality-based filtering of alignments.

Main Methods:

More Related Videos

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
11:04

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

Published on: May 19, 2019

Related Experiment Videos

Last Updated: May 11, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
11:04

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

Published on: May 19, 2019

  • ARDEN utilizes real experimental reads and an artificially generated reference genome.
  • It enables dataset-specific computation of error rates.
  • The method facilitates the construction of receiver operating characteristic (ROC) curves for performance evaluation.

Main Results:

  • ARDEN provides accurate estimation of read mapping error rates using real data.
  • Demonstrated utility in general read mapper comparisons and parameter optimization.
  • Application in single-nucleotide polymorphism discovery significantly reduced false positive identifications.

Conclusions:

  • ARDEN offers a robust, dataset-specific method for evaluating read mapping accuracy.
  • The tool aids in optimizing NGS data processing pipelines and improving the reliability of downstream analyses.
  • ARDEN is freely available, promoting its adoption in the research community.