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 Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Sanger Sequencing01:57

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...

You might also read

Related Articles

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

Sort by
Same author

Peripheral complement C4 protein in schizophrenia: Association with gene copy number and immune cell subtypes.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Multi-platform framework for mapping somatic retrotransposition in human tissues.

bioRxiv : the preprint server for biology·2025
Same author

Single cell whole genome and transcriptome sequencing links somatic mutations to cell identity and ancestry.

bioRxiv : the preprint server for biology·2025
Same author

Peripheral Complement C4 Protein in Schizophrenia: Association with Gene Copy Number and Immune Cell Subtypes.

bioRxiv : the preprint server for biology·2025
Same author

The Somatic Mosaicism across Human Tissues Network.

Nature·2025
Same author

Cell-type specific global reprogramming of the transcriptome and epigenome in induced neurons with the 16p11.2 neuropsychiatric CNVs.

European journal of human genetics : EJHG·2025
Same journal

pGWAS-Portal: a comprehensive online platform for integrative post-genome-wide association study analysis.

BMC genomics·2026
Same journal

Physiological and transcriptomic analyses of Rosa persica in response to drought stress and functional validation of the transcription factor RpERF113-like.

BMC genomics·2026
Same journal

Integrated analysis of chromatin accessibility and transcriptome profiles in granulosa cells of sheep with different FecB genotypes.

BMC genomics·2026
Same journal

Correction: TB-DROP: deep learning-based drug resistance prediction of Mycobacterium tuberculosis utilizing whole genome mutations.

BMC genomics·2026
Same journal

Chromosomal scale genome assembly of medicinal plant Sophora tonkinensis.

BMC genomics·2026
Same journal

Variant-specific RNA testing resolves variants of uncertain significance in exome testing.

BMC genomics·2026
See all related articles

Related Experiment Video

Updated: May 30, 2026

Using Next Generation Sequencing to Identify Mutations Associated with Repair of a CAS9-induced Double Strand Break Near the CD4 Promoter
06:59

Using Next Generation Sequencing to Identify Mutations Associated with Repair of a CAS9-induced Double Strand Break Near the CD4 Promoter

Published on: March 31, 2022

Identification of genomic indels and structural variations using split reads.

Zhengdong D Zhang1, Jiang Du, Hugo Lam

  • 1Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA. zhengdong.zhang@einstein.yu.edu

BMC Genomics
|July 27, 2011
PubMed
Summary
This summary is machine-generated.

We developed SRiC, a new method for detecting structural variants (SVs) in the human genome. Our approach calibrates calls using simulated data, providing a more accurate estimate of ~670,000 indels/SVs per individual genome.

More Related Videos

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

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
11:11

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Published on: August 24, 2017

Related Experiment Videos

Last Updated: May 30, 2026

Using Next Generation Sequencing to Identify Mutations Associated with Repair of a CAS9-induced Double Strand Break Near the CD4 Promoter
06:59

Using Next Generation Sequencing to Identify Mutations Associated with Repair of a CAS9-induced Double Strand Break Near the CD4 Promoter

Published on: March 31, 2022

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

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
11:11

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Published on: August 24, 2017

Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Structural variants (SVs) like insertions and deletions are genetically significant in humans.
  • Next-generation sequencing enables high-throughput, whole-genome SV surveys.
  • Existing SV detection methods have biases due to experimental and computational limitations.

Purpose of the Study:

  • To present SRiC, a novel sequence-based method for accurate structural variant detection.
  • To address biases in current SV calling methods.
  • To provide an unbiased estimate of SVs in the human genome.

Main Methods:

  • SRiC uses gapped alignment to map reads to a reference genome.
  • It scores mappings considering sequencing and alignment errors, prioritizing central gaps.
  • Calibration against simulated data with realistic error models quantifies sensitivity and positive predictive value for different SV types.

Main Results:

  • SRiC was tested on 1000 Genomes Project data.
  • Analysis of chromosome 1 and simulation calibrations yielded an unbiased SV estimate.
  • An individual human genome is estimated to contain approximately 670,000 indels/SVs.

Conclusions:

  • SRiC precisely identifies SV breakpoints and insertion sequences, unlike read-depth and read-pair methods.
  • The method covers the full spectrum of deletion sizes.
  • SRiC is expected to be further enhanced by third-generation sequencing technologies with longer reads.