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

Genetic Variation01:25

Genetic Variation

241
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,...
241
Variability: Analysis01:11

Variability: Analysis

116
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...
116
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.6K
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...
5.6K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

16.8K
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%...
16.8K
Exon Recombination02:32

Exon Recombination

3.5K
The evolution of new genes is critical for speciation. Exon recombination, also known as exon shuffling or domain shuffling, is an important means of new gene formation. It is observed across vertebrates, invertebrates, and in some plants such as potatoes and sunflowers. During exon recombination, exons from the same or different genes recombine and produce new exon-intron combinations, which might evolve into new genes. 
Exon shuffling follows “splice frame rules.” Each exon...
3.5K
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

57.6K
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).
57.6K

You might also read

Related Articles

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

Sort by
Same author

The Kenyan Human Gut Virome Catalogue reveals extensive viral diversity and age-dependent community structure.

Scientific reports·2026
Same author

DeepTaxa: a hybrid CNN-BERT framework for 16S rRNA taxonomic classification.

Bioinformatics advances·2026
Same author

Type I interferon-activated NK cells control polycythemia vera in vivo.

Blood·2026
Same author

EMImR: a Shiny application for identifying transcriptomic and epigenomic changes.

GigaByte (Hong Kong, China)·2026
Same author

MARVpred: machine learning prediction of inhibitors targeting Marburg virus Gene 4 Small ORF protein.

BMC infectious diseases·2026
Same author

RareInsight simplifies the communication of genetic results for rare disease patients.

Scientific reports·2025
Same journal

Application of ephrin-B2 loaded glycol chitosan-silk fibroin hydrogel in the treatment of diabetic refractory wounds.

Scientific reports·2026
Same journal

International expert Delphi consensus on thromboprophylaxis in metabolic and bariatric surgery.

Scientific reports·2026
Same journal

Assessing the cross-region knowledge transfer capability of selected deep learning building vectorization methods in the context of available training datasets.

Scientific reports·2026
Same journal

Feasibility and preliminary effects of outdoor versus indoor cognitive-motor therapy in women with Alzheimer's disease: A randomized single-blind pilot study.

Scientific reports·2026
Same journal

Hallmarks of social action in the vocal turn-taking of wild common marmosets (Callithrix jacchus).

Scientific reports·2026
Same journal

Role and mechanism of AOPPs-induced NOX4-mediated ferroptosis in intervertebral disc degeneration.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: May 15, 2025

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
08:00

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Published on: October 11, 2019

7.4K

Efficient and easy gene expression and genetic variation data analysis and visualization using exvar.

Hiba Ben Aribi1, Imraan Dixon2, Najla Abassi3

  • 1Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia. benaribi.hiba@gmail.com.

Scientific Reports
|April 10, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces "exvar," a user-friendly R package simplifying RNA sequencing analysis for gene expression and variant calling. It integrates multiple tools for easier genomic data analysis and visualization across species.

Keywords:
CNVsExvarGene expressionIndelsR packageSNPsVariants calling

More Related Videos

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

2.6K
Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
07:15

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

10.9K

Related Experiment Videos

Last Updated: May 15, 2025

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
08:00

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Published on: October 11, 2019

7.4K
Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

2.6K
Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
07:15

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

10.9K

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • RNA sequencing (RNA-seq) data analysis is complex, requiring specialized skills and tools.
  • Existing workflows present challenges for researchers, necessitating integrated and user-friendly solutions.
  • Genomic data analysis and visualization tools are crucial for advancing biological research.

Purpose of the Study:

  • To develop a novel R package simplifying RNA sequencing data analysis.
  • To integrate gene expression analysis and genetic variant calling functionalities.
  • To provide user-friendly data visualization tools for genomic data.

Main Methods:

  • Developed a new R package, "exvar", utilizing existing CRAN and Bioconductor packages.
  • Implemented functions for gene expression analysis and genetic variant calling from RNA-seq data.
  • Integrated three data visualization Shiny applications within the R package.

Main Results:

  • The "exvar" package successfully performs gene expression analysis and genetic variant calling.
  • Validated the pipeline using multiple public RNA-seq datasets across various species.
  • The package offers integrated data analysis and visualization capabilities.

Conclusions:

  • The "exvar" R package provides a streamlined and integrated solution for RNA-seq data analysis.
  • It enhances accessibility to complex genomic data analysis for a broader research community.
  • The package supports multi-species analysis, increasing its utility and applicability.