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Related Concept Videos

Genetic Variation01:25

Genetic Variation

1.4K
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,...
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What is Variation?01:14

What is Variation?

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Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
The range, standard deviation, standard error, and variance are the different measures of variation.
Range: The range is the difference between its maximum and...
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Variation: Normal Distribution, Range, and Standard Deviation02:32

Variation: Normal Distribution, Range, and Standard Deviation

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In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
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Conservative Site-specific Recombination and Phase Variation02:53

Conservative Site-specific Recombination and Phase Variation

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Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
The recognition sites for Cre recombinase called LoxP...
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Variation01:19

Variation

8.0K
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
8.0K
Variation of Atmospheric Pressure01:18

Variation of Atmospheric Pressure

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Change in atmospheric pressure with height is particularly interesting. The decrease in atmospheric pressure with increasing altitude is due to the decreasing gravitational force per unit area as we move away from the surface of the earth.
Assuming the air temperature is constant at a given altitude and that the ideal gas law of thermodynamics describes the atmosphere to a good approximation, one can find the variation of atmospheric pressure with height.
Let p(y) be the atmospheric pressure at...
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Related Experiment Video

Updated: Feb 6, 2026

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

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Variation graph toolkit improves read mapping by representing genetic variation in the reference.

Erik Garrison1, Jouni Sirén1, Adam M Novak2

  • 1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.

Nature Biotechnology
|August 21, 2018
PubMed
Summary
This summary is machine-generated.

Variation graphs represent genomic diversity better than linear references, improving DNA sequencing accuracy. The vg toolkit enables practical use of these graphs for large-scale genome analysis and de novo assemblies.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Linear reference genomes fail to capture population-level genetic variation, leading to biased DNA sequence interpretation and read mapping.
  • Existing graph genome software has faced challenges with scalability and topological complexity, limiting their practical application.

Discussion:

  • The vg toolkit offers a scalable solution for constructing and utilizing variation graphs as comprehensive genomic references.
  • It employs generalized compressed suffix arrays for efficient read mapping to complex graphs, surpassing linear reference alignment accuracy.
  • This approach effectively mitigates reference bias inherent in traditional methods.

Key Insights:

  • Variation graphs provide a more accurate representation of individual genomes by incorporating population diversity.
  • The vg toolkit facilitates the practical application of graph genomes at the human genome scale (gigabase).
  • Improved read mapping accuracy and bias reduction are key benefits of using vg with variation graphs.

Outlook:

  • Enables more accurate and comprehensive analysis of DNA sequencing data across diverse populations.
  • Facilitates de novo genome assembly with greater topological complexity.
  • Advances the field of personalized genomics and population genetics research.