Related Experiment Video
Updated: Jun 5, 2026
09:45
Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
Accuracy of CNV Detection from GWAS Data.
Dandan Zhang1, Yudong Qian, Nirmala Akula
1Department of Pathology, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Plos One
|January 21, 2011
Summary
This study evaluated four copy number variant (CNV) detection software suites, finding Birdsuite and Partek performed best for rare CNVs. However, CNV calling algorithms, especially for common variants, require significant improvement.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Copy number variants (CNVs) are crucial in genetic variation and disease.
- Genome-wide SNP arrays are widely used for CNV detection.
- Multiple software suites exist, necessitating performance evaluation.
Purpose of the Study:
- To assess the performance of four CNV detection software suites: Birdsuite, Partek, HelixTree, and PennCNV-Affy.
- To compare their accuracy in identifying both rare and common CNVs using established datasets and clinical data.
Main Methods:
- Evaluated software recovery rates using known CNVs from HapMap samples (sequencing and aCGH).
- Assessed CNV calling accuracy in the Bipolar Genome Study (BiGS) dataset using Affymetrix SNP 6.0 array.
- Validated CNV calls using quantitative real-time PCR (qPCR).
Main Results:
- Birdsuite showed the highest recovery of large HapMap CNVs; recovery increased with decreased CNV frequency.
- Birdsuite and Partek demonstrated superior positive predictive values for rare CNVs.
- Inconsistent accuracy was observed for common CNVs, highlighting algorithmic limitations.
Conclusions:
- Current CNV calling algorithms, particularly for common variants, require substantial improvement.
- A definitive 'gold standard' for CNV detection is yet to be established.
- Software performance varies, with Birdsuite and Partek showing promise for rare CNV identification.
Related Concept Videos
01:11Genome-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...
GWAS does not require the identification of the target gene involved in...
02:26Comparing 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%...
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%...
01:05Single 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,...