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Related Concept Videos

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%...
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,...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Related Experiment Video

Updated: Jun 30, 2026

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

SNP genotyping and parameter estimation in polyploids using low-coverage sequencing data.

Paul D Blischak1, Laura S Kubatko1,2, Andrea D Wolfe1

  • 1Department of Evolution, Ecology, and Organismal Biology.

Bioinformatics (Oxford, England)
|October 14, 2017
PubMed
Summary
This summary is machine-generated.

New models improve genotyping and population genetic parameter estimation for polyploids, outperforming existing methods especially with low sequencing coverage. This advances population genomic inferences in diverse plant and animal species.

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Area of Science:

  • Population genetics
  • Genomics
  • Bioinformatics

Background:

  • Standard diploid genetic methods are insufficient for polyploid organisms due to duplicated chromosomes and complex inheritance.
  • Whole genome duplication (WGD) events in autopolyploids and allopolyploids create unique genetic challenges.

Purpose of the Study:

  • To develop and evaluate novel models for accurate genotype and population genetic parameter estimation in polyploids.
  • To address limitations of existing methods when applied to polyploid high-throughput sequencing data.

Main Methods:

  • Developed two new models for genotype likelihoods in autopolyploids and allopolyploids.
  • Utilized simulations to compare new models against existing approaches across various sequencing coverages and ploidy levels.
  • Applied models to empirical datasets from scientific literature.

Main Results:

  • The new models demonstrated lower estimation errors for genotypes and population genetic parameters compared to existing methods.
  • Improved performance was particularly evident under low sequencing coverage scenarios.
  • Successful application to real-world polyploid genomic datasets was achieved.

Conclusions:

  • Genotype likelihoods effectively model non-standard inheritance patterns in polyploids.
  • The developed models offer a promising approach for robust population genomic inferences in polyploid species.
  • An open-source C++ program, EBG, is available for implementing these models.