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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...
Sanger Sequencing01:57

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...

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Related Experiment Video

Updated: Jun 23, 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 detection for massively parallel whole-genome resequencing.

Ruiqiang Li1, Yingrui Li, Xiaodong Fang

  • 1Beijing Genomics Institute at Shenzhen, Shenzhen 518000, China

Genome Research
|May 8, 2009
PubMed
Summary

This study introduces a new method for accurate SNP detection and consensus calling using Illumina sequencing. The approach ensures high accuracy and genome coverage, improving genetic variation analysis.

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Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Related Experiment Videos

Last Updated: Jun 23, 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

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Next-generation sequencing (NGS) offers high throughput and lower costs compared to Sanger sequencing.
  • Studying genetic variation via whole-genome or targeted resequencing is a key NGS application.

Purpose of the Study:

  • To develop a robust consensus-calling and SNP-detection method for Illumina sequencing-by-synthesis technology.
  • To address data quality, alignment, and experimental errors inherent in this technology.

Main Methods:

  • Integrated base quality, alignment, and error data into a single Bayesian quality score for consensus accuracy.
  • Applied the method to a large-scale human resequencing dataset with 36x coverage.
  • Utilized prior probabilities of dbSNP alleles for improved SNP site coverage at low sequencing depths.

Main Results:

  • Assembled a high-quality consensus sequence covering 92.25% of diploid autosomes and 88.07% of the X chromosome.
  • Achieved high consistency with existing genotype data: 99.97% on the X chromosome and 99.84% on autosomes.
  • Demonstrated a very low false call rate and excellent genome coverage across various sequencing depths.

Conclusions:

  • The developed method provides accurate SNP detection and consensus calling for Illumina sequencing data.
  • The approach enhances genome coverage and accuracy, particularly beneficial for genetic variation studies.
  • The method shows promise for improving the analysis of genetic variation at both high and low sequencing depths.