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

17.7K
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%...
17.7K
Genetic Variation01:25

Genetic Variation

282
Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles,...
282
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

15.1K
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,...
15.1K
Variability: Analysis01:11

Variability: Analysis

143
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
143
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.7K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.7K
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

58.4K
In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
58.4K

You might also read

Related Articles

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

Sort by
Same author

Convergent evolution of the N156K mutation in A(H1N1)pdm09 hemagglutinin contributes to antigenic drift and cluster transition.

Emerging microbes & infections·2026
Same author

Intratumoral <i>Parvimonas micra</i> promotes esophageal squamous cell carcinoma via <i>p</i>-cresol-induced T<sub>reg</sub> differentiation.

Science advances·2026
Same author

ResMicroDb: a comprehensive database and analysis platform for the human respiratory microbiome.

Nucleic acids research·2025
Same author

Characterization of the extrinsic and intrinsic signatures and therapeutic vulnerability of small cell lung cancers.

Signal transduction and targeted therapy·2025
Same author

Benefits and challenges of host depletion methods in profiling the upper and lower respiratory microbiome.

NPJ biofilms and microbiomes·2025
Same author

A fuzzy sequencer for rapid DNA fragment counting and genotyping.

Nature biomedical engineering·2025

Related Experiment Video

Updated: Jul 1, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

962

PySNV for complex intra-host variation detection.

Liandong Li1, Haoyi Fu1,2, Wentai Ma1,2

  • 1Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing 100101, China.

Bioinformatics (Oxford, England)
|March 1, 2024
PubMed
Summary
This summary is machine-generated.

We developed PySNV, a new tool to detect complex intra-host variants, including long indels and low-frequency mutations, outperforming existing software in accuracy and consistency for pathogen and tumor evolution studies.

More Related Videos

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
18:10

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency

Published on: June 16, 2011

29.6K
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

15.2K

Related Experiment Videos

Last Updated: Jul 1, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

962
Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
18:10

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency

Published on: June 16, 2011

29.6K
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

15.2K

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Intra-host variants are genetic variations within an organism, crucial for understanding pathogen evolution and somatic mutations in diseases like cancer.
  • Identifying complex intra-host variants, such as long insertions/deletions and mixed mutation types, remains a significant challenge.
  • Current variant detection software performance on complex intra-host variants is largely unknown.

Purpose of the Study:

  • To evaluate the performance of existing variant detection software on complex intra-host variants.
  • To develop a novel computational tool, PySNV, for accurate and efficient detection of complex intra-host variations.
  • To validate PySNV's performance on simulated and real-world sequencing data, including SARS-CoV-2.

Main Methods:

  • Simulated a dataset with 1869 intra-host variants exhibiting diverse mutation patterns.
  • Benchmarked existing variant detection software against the simulated dataset.
  • Developed PySNV, a new software tool for complex intra-host variant detection.
  • Validated PySNV on simulated data and SARS-CoV-2 replicate sequencing data.

Main Results:

  • Existing software showed limited performance in detecting long indels and low-frequency variants.
  • PySNV achieved a 0.99 F1-score and 0.99 Pearson correlation coefficient on simulated data, accurately detecting complex variants.
  • PySNV identified 21% more variants than the best benchmarked software (LoFreq) on SARS-CoV-2 data, with improved consistency.

Conclusions:

  • PySNV demonstrates superior performance in detecting complex intra-host variants, including low-frequency and long indel mutations.
  • The tool offers high accuracy and consistency, outperforming current methods on both simulated and real sequencing data.
  • PySNV provides a robust solution for advancing research in pathogen evolution, tumor biology, and other fields studying intra-host genetic diversity.