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Comparing Copy Number Variations and SNPs

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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DNA Microarrays

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The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are characterized.

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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 18, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

Joint estimation of DNA copy number from multiple platforms.

Nancy R Zhang¹, Yasin Senbabaoglu, Jun Z Li

¹Department of Statistics, Stanford University, Stanford, CA, USA. nzhang@stanford.edu

Bioinformatics (Oxford, England)

|November 26, 2009

Summary

This study introduces Multi-Platform Circular Binary Segmentation (MPCBS), a novel method for integrating DNA copy number variant (CNV) data from multiple platforms. MPCBS improves spatial resolution and detection power for CNVs, offering a consensus profile without pre-standardization.

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Detection of Copy Number Alterations Using Single Cell Sequencing

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Measuring Single-Cell Mitochondrial DNA Copy Number and Heteroplasmy Using Digital Droplet Polymerase Chain Reaction

Measuring Single-Cell Mitochondrial DNA Copy Number and Heteroplasmy Using Digital Droplet Polymerase Chain Reaction

Published on: July 12, 2022

Area of Science:

Genomics and Bioinformatics
Statistical Genetics
Computational Biology

Background:

DNA copy number variants (CNVs) are crucial genetic variations involving chromosomal segment gains or losses.
High-throughput microarray techniques are used for DNA copy number measurement, often involving multiple platforms or versions.
Integrating data from diverse platforms is necessary for a consensus molecular profile but lacks robust statistical methods for inter-platform differences.

Purpose of the Study:

To develop a statistical method for integrated analysis of DNA copy number data from multiple platforms.
To address challenges in combining data due to probe coverage, assay methods, sensitivity, and analytical complexity differences.
To improve the accuracy, resolution, and detection power of CNV analysis across different technical sources.

Main Methods:

Proposed Multi-Platform Circular Binary Segmentation (MPCBS), a method that pools statistical evidence across platforms during segmentation.
MPCBS utilizes a weighted sum of t-statistics derived from a generalized log-likelihood ratio of a multi-platform model.
The method does not require pre-standardization of data from different sources.

Main Results:

MPCBS demonstrated improved spatial resolution and detection power compared to conventional approaches when analyzing integrated Affymetrix, Illumina, Agilent, and fosmid clone data on HapMap samples.
The method provides a natural consensus across different platforms.
MPCBS was successfully applied to analyze multi-platform tumor sample data.

Conclusions:

MPCBS offers a statistically sound approach for integrated CNV analysis across diverse platforms.
The method enhances the accuracy and resolution of CNV detection, yielding a reliable consensus profile.
The R package for MPCBS is available on R-Forge.