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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,...
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...
Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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Related Experiment Video

Updated: Jun 15, 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

High quality SNP calling using Illumina data at shallow coverage.

Nawar Malhis1, Steven J M Jones

  • 1Genome Sciences Centre, BC Cancer Agency, Vancouver BC, Canada. nmalhis@bcgsc.ca

Bioinformatics (Oxford, England)
|March 2, 2010
PubMed
Summary
This summary is machine-generated.

Slider II improves single nucleotide polymorphism (SNP) detection from second generation sequencing (SGS) data. This alignment and SNP calling approach increases called SNPs and reduces false positives, especially with shallow coverage.

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Targeted DNA Methylation Analysis by Next-generation Sequencing
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Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

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Last Updated: Jun 15, 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

Targeted DNA Methylation Analysis by Next-generation Sequencing
08:38

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Single nucleotide polymorphism (SNP) detection is crucial for second generation sequencing (SGS) data analysis.
  • Accurate SNP calling is challenging due to sequencing quality and reference genome properties, particularly with shallow coverage data.

Purpose of the Study:

  • To present Slider II, an advanced alignment and SNP calling approach.
  • To improve the accuracy and yield of SNP detection from SGS data.

Main Methods:

  • Developed Slider II, an alignment and SNP calling algorithm.
  • Implemented optional prior utilization of known SNPs to enhance detection capabilities.

Main Results:

  • Slider II demonstrates improved algorithmic approaches for SNP detection.
  • Achieved a higher number of called SNPs with a reduced false positive rate.

Conclusions:

  • Slider II offers enhanced SNP and mutation detection, especially for shallow coverage data.
  • The optional use of known SNPs as priors further boosts detection accuracy for known and novel variants.