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

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

19.3K
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%...
19.3K
Next-generation Sequencing03:00

Next-generation Sequencing

101.7K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
101.7K
RNA-seq03:21

RNA-seq

12.6K
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...
12.6K

You might also read

Related Articles

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

Sort by
Same author

[Expression of eosinophil major basic protein and neutrophil elastase in nasal polyp tissue and secretion].

Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery·2008
Same author

[Effect of interferon-gamma on the expression of vascular endothelial growth factor C on Hep-2 laryngeal carcinoma cell lines].

Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery·2008
Same author

Effects of 18alpha-glycyrrhizin on the pharmacodynamics and pharmacokinetics of glibenclamide in alloxan-induced diabetic rats.

European journal of pharmacology·2008
Same author

[Inhibition of oxidative activity of myeloperoxidase by anti-myeloperoxidase antibodies from patients with microscopic polyangiitis].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences·2008
Same author

Gene delivery of indoleamine 2,3-dioxygenase prolongs cardiac allograft survival by shaping the types of T-cell responses.

The journal of gene medicine·2008
Same author

[Ultrasonographic findings of intussusception complicated by intestinal necrosis in children].

Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics·2008

Related Experiment Video

Updated: Apr 7, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

12.3K

Modeling the next generation sequencing read count data for DNA copy number variant study.

Tieming Ji, Jie Chen

    Statistical Applications in Genetics and Molecular Biology
    |July 4, 2015
    PubMed
    Summary

    This study introduces a Bayesian statistical model to detect DNA copy number variants (CNVs) using next-generation sequencing (NGS) data. The method effectively identifies CNV regions, crucial for understanding genetic disorders and cancer development.

    More Related Videos

    Targeted DNA Methylation Analysis by Next-generation Sequencing
    08:38

    Targeted DNA Methylation Analysis by Next-generation Sequencing

    Published on: February 24, 2015

    38.3K
    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

    17.5K

    Related Experiment Videos

    Last Updated: Apr 7, 2026

    Detection of Copy Number Alterations Using Single Cell Sequencing
    09:45

    Detection of Copy Number Alterations Using Single Cell Sequencing

    Published on: February 17, 2017

    12.3K
    Targeted DNA Methylation Analysis by Next-generation Sequencing
    08:38

    Targeted DNA Methylation Analysis by Next-generation Sequencing

    Published on: February 24, 2015

    38.3K
    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

    17.5K

    Area of Science:

    • Genomics
    • Bioinformatics
    • Statistical Genetics

    Background:

    • Next-generation sequencing (NGS) advances biomedical research by enabling genetic information discovery.
    • DNA copy number variants (CNVs) are implicated in cancer, genetic disorders, and disease development.
    • Analyzing NGS data for CNVs is critical for genomic research.

    Purpose of the Study:

    • To develop a statistical change point model for detecting CNV boundaries in NGS read count data.
    • To utilize a Bayesian approach for parameter change incorporation in NGS data analysis.
    • To provide a robust method for identifying CNV regions in genomic datasets.

    Main Methods:

    • A statistical change point model was formulated for NGS read count data.
    • A Bayesian approach was employed to model parameter changes in read count distributions.
    • Posterior probabilities were derived for change point inferences.

    Main Results:

    • The proposed Bayesian model demonstrated advantages in extensive simulation studies.
    • The method successfully identified CNV regions in a publicly available lung cancer cell line NGS dataset.
    • The model provides accurate detection of CNV boundaries.

    Conclusions:

    • The developed statistical change point model is effective for CNV detection using NGS data.
    • The Bayesian approach enhances the accuracy and robustness of CNV analysis.
    • This method aids in understanding the role of CNVs in diseases like cancer.