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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%...
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Genome Copying Errors

DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger their  survival. Therefore, the copying errors are checked and repaired at three levels.
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,...

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Related Experiment Video

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Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

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Published on: February 17, 2017

Effective normalization for copy number variation detection from whole genome sequencing.

Angel Janevski1, Vinay Varadan, Sitharthan Kamalakaran

  • 1Philips Research, 345 Scarborough Rd, Briarcliff Manor, NY 10510, USA. angel.janevski@philips.com

BMC Genomics
|November 9, 2012
PubMed
Summary
This summary is machine-generated.

Choosing the right normalization method significantly impacts copy number variation (CNV) detection. Using genomic mappability or a control genome optimizes CNV analysis results from whole genome sequencing data.

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Whole genome sequencing (WGS) offers high-resolution genomic insights.
  • Copy number variation (CNV) detection tools have configurable parameters.
  • The impact of normalization on CNV estimates is not well understood.

Purpose of the Study:

  • To evaluate the effect of normalization methodologies on CNV detection.
  • To compare FREEC and CNV-seq algorithms using WGS data.
  • To analyze normalization impacts across different genomic regions.

Main Methods:

  • Applied FREEC and CNV-seq to 8 WGS datasets.
  • Evaluated GC content, mappability, and control genome normalization in FREEC.
  • Assessed concordance of CNV calls between methods and configurations.

Main Results:

  • GC content normalization yielded the most altered copy number regions.
  • Mappability and control genome normalization reduced the number and length of CNV regions.
  • Mappability normalization significantly reduced deletion CNV calls; CNV-seq showed comparable results.

Conclusions:

  • Normalization methodology choice substantially affects CNV calls.
  • Genomic mappability or control genome normalization can optimize CNV analysis.
  • Selecting appropriate normalization is crucial for accurate CNV detection.