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Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
Comparative analyses of seven algorithms for copy number variant identification from single nucleotide polymorphism
Andrew E Dellinger1, Seang-Mei Saw, Liang K Goh
1Center for Human Genetics, Duke University Medical Center, Durham, NC 27710, USA.
Nucleic Acids Research
|February 10, 2010
Summary
This study compared seven copy number variant (CNV) detection methods using SNP array data. QuantiSNP demonstrated superior performance, showing better accuracy in identifying genetic variations linked to diseases.
Area of Science:
- Genetics
- Bioinformatics
- Genomic Analysis
Background:
- Copy number variants (CNVs) are increasingly utilized in genetic disease association studies.
- Existing CNV detection methods exhibit variations in thresholds and characteristics, necessitating comparative evaluation.
Purpose of the Study:
- To evaluate and compare the performance of seven distinct CNV detection algorithms.
- To introduce and validate the normalized singleton ratio (NSR) as a metric for parameter optimization.
Main Methods:
- Comparative analysis of seven CNV detection methods: circular binary segmentation, CNVFinder, cnvPartition, gain and loss of DNA, Nexus algorithms, PennCNV, and QuantiSNP.
- Utilized real and simulated data from Illumina and Affymetrix platforms.
- Employed normalized singleton ratio (NSR) for parameter optimization and receiver operating characteristic (ROC) curve residuals for performance evaluation.
Main Results:
- QuantiSNP generally outperformed other methods based on ROC curve residuals across various datasets.
- Optimal parameters, determined by NSR and ROC residuals, remained consistent across different data types.
- Nexus Rank and SNPRank showed high power but low specificity, with Nexus Rank identifying large CNVs.
Conclusions:
- QuantiSNP is a highly effective method for CNV detection in SNP array data.
- NSR serves as a reliable metric for optimizing CNV detection parameters.
- Method selection impacts CNV detection accuracy, highlighting the importance of choosing appropriate algorithms for genetic studies.
Related Concept Videos
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,...