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Comparing Copy Number Variations and SNPs

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-SNPs

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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,...

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Related Experiment Video

Updated: Oct 8, 2025

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Benchmarking small-variant genotyping in polyploids.

Daniel P Cooke¹, David C Wedge², Gerton Lunter^1,3

¹MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, United Kingdom.

Genome Research

|December 30, 2021

Summary

This summary is machine-generated.

Genotyping polyploid plants using sequencing has lacked benchmarks. A new study shows the Octopus tool significantly reduces genotyping errors in polyploids compared to other methods, improving molecular breeding accuracy.

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Published on: June 23, 2012

Area of Science:

Genomics
Plant Breeding
Bioinformatics

Background:

Genotyping from sequencing is crucial for polyploid plant molecular breeding.
Existing benchmarks for genotyping accuracy are limited for polyploids, unlike diploids.
Accurate genotyping in polyploids is essential for advancing breeding strategies.

Purpose of the Study:

To evaluate genotyping error rates for polyploid plants using real sequencing data.
To benchmark the performance of the Octopus variant calling method against other popular tools.
To establish benchmarks for assessing genotyping accuracy in polyploid variant calling.

Main Methods:

In silico mixtures of diploid Genome in a Bottle (GIAB) samples were used to create tetraploid and hexaploid datasets.
Whole-genome sequencing data from these simulated polyploids were analyzed.
The Octopus variant calling method was evaluated alongside other popular genotyping tools.
Concordance analysis was performed on real autotriploid banana datasets.

Main Results:

Genotyping errors are prevalent in polyploid datasets at typical sequencing depths.
Octopus demonstrated a 25% reduction in genotyping errors on average compared to other methods.
Benchmarks were established for evaluating genotyping accuracy in polyploid variant calling.

Conclusions:

Octopus offers improved accuracy for genotyping small variants in polyploid plants.
The developed benchmarks are vital for assessing and improving polyploid genotyping tools.
This work facilitates more reliable molecular breeding in polyploid species.