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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%...

Next-generation Sequencing

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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.

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Related Experiment Video

Updated: May 23, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

CONTRA: copy number analysis for targeted resequencing.

Jason Li¹, Richard Lupat, Kaushalya C Amarasinghe

¹Bioinformatics Core Facility, Peter MacCallum Cancer Centre, VIC 3002, Australia. Jason.Li@petermac.org

Bioinformatics (Oxford, England)

|April 5, 2012

Summary

This summary is machine-generated.

A new method called CONTRA improves copy number variation (CNV) detection for targeted resequencing (TR) data. This robust analysis maximizes the value of TR for identifying disease-causing genetic variants.

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Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

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Published on: April 11, 2016

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Targeted resequencing (TR) is increasingly used for cost-effective variant identification.
A robust method for copy number variation (CNV) analysis is crucial for TR data.
Existing methods may not fully leverage the potential of TR for CNV detection.

Purpose of the Study:

To develop and present a novel method for CNV detection specifically designed for TR data.
To enhance the utility of targeted resequencing by enabling accurate CNV analysis.
To provide a software package for seamless integration into existing next-generation sequencing workflows.

Main Methods:

Developed a CNV detection method using normalized depth of coverage for TR data.
Implemented strategies to correct for GC-content bias and library size effects.
Utilized base-level log-ratios, binning, and interpolation for accurate log-ratio estimation.
Created the CONTRA software package for CNV analysis of TR data.

Main Results:

The CONTRA method accurately calls copy number gains and losses in target regions.
Validated the method using diverse target enrichment assays, simulated data, and real germline data.
Demonstrated the effectiveness of bias correction and log-ratio estimation strategies.
CONTRA outputs results in VCF4.0 format for easy integration.

Conclusions:

The presented method provides a robust approach for CNV detection in targeted resequencing data.
CONTRA software facilitates the analysis of CNVs from TR, including whole-exome capture data.
This advancement increases the value of targeted resequencing for genetic variant discovery.