Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: May 21, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Analysis of insertion-deletion from deep-sequencing data: software evaluation for optimal detection.

Joseph A Neuman¹, Ofer Isakov, Noam Shomron

¹Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.

Briefings in Bioinformatics

|June 19, 2012

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

Exploring per-base quality scores as a surrogate marker of cell-free DNA fragmentome.

Briefings in bioinformatics·2026

Same author

Opposite molecular sex correlations in tauopathy paralleled by motor and cognitive efficacy of davunetide in women.

Molecular psychiatry·2026

Same author

FOXM1 expression is induced by the brain microenvironment and supports CRC brain metastatic adaptation.

Clinical & experimental metastasis·2026

Same author

Gut microbiota composition correlates with PBMC microRNA expression following maximal exercise testing in endurance athletes.

Frontiers in microbiomes·2026

Same author

Evaluating the Impact of ClinGen Variant Curation Expert Panel Criteria Specifications on Variant Interpretation across Multiple Genes.

The Journal of molecular diagnostics : JMD·2026

Same author

Artificial Intelligence Does Not Always Win.

The Israel Medical Association journal : IMAJ·2026

Same journal

K-attention: a biologically informed attention operator for data-efficient sequence-based omics modeling.

Briefings in bioinformatics·2026

Same journal

Accurate prediction of asparagine deamidation in biologics using advanced machine learning models.

Briefings in bioinformatics·2026

Same journal

scImmuneCo: a compendium of cell-type-specific functional modules for decoding immune responses from single-cell RNA-seq data.

Briefings in bioinformatics·2026

Same journal

scGenoByte: a GenoByte embedding transformer with biological priors for cell type annotation.

Briefings in bioinformatics·2026

Same journal

FerroScore: a statistical approach for quantifying tumor-related ferroptosis based on omics data.

Briefings in bioinformatics·2026

Same journal

METEOR: a data-adaptive Mendelian randomization method for powerful detection of shared and specific exposures underlying multiple outcomes.

Briefings in bioinformatics·2026

See all related articles

This study evaluates indel calling software for detecting short insertion/deletion mutations in human genomes. It provides insights into tool selection and experimental design for accurate variant detection using deep sequencing data.

Area of Science:

Genomics
Bioinformatics
Human Genetics

Background:

Insertion and deletion (indel) mutations are common structural variations impacting human traits and diseases.
Deep sequencing technologies generate massive data crucial for mutation detection, including indels.
Computational analysis of deep-sequencing data is essential for accurate indel calling.

Purpose of the Study:

To evaluate the performance of various indel calling software for short indel (1-10 nt) detection.
To understand inter-software differences and their impact on downstream analysis.
To identify key features for successful experimental design and tool selection in indel detection.

Main Methods:

Comparative analysis of multiple indel calling software.

More Related Videos

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Published on: August 24, 2017

Related Experiment Videos

Last Updated: May 21, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Published on: August 24, 2017

Evaluation of sensitivity and predictive values under varying parameters (read depth, read length, indel size, frequency).

Assessment of short indel detection (1-10 nt).

Main Results:

Software selection significantly influences indel calling results.
Performance metrics (sensitivity, predictive values) vary based on parameters like read depth and indel frequency.
Identified key factors influencing the accuracy of indel detection.

Conclusions:

Understanding software limitations is crucial for accurate indel detection.
Guidance provided for experimental design and appropriate tool selection in genomic studies.
This evaluation serves as a foundation for future assessments of indel calling methods.