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Updated: Jun 6, 2026

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Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization
Valentina Boeva1, Andrei Zinovyev, Kevin Bleakley
1Institut Curie, INSERM, U900, Paris, France. freec@curie.fr
Bioinformatics (Oxford, England)
|November 18, 2010
Summary
We developed FREEC, a tool for copy number alteration (CNA) detection in cancer studies using deep-sequencing data. It addresses challenges like missing control samples and polyploidy, enabling accurate CNA calling.
Area of Science:
- Genomics
- Bioinformatics
- Cancer Research
Background:
- Cancer deep-sequencing data analysis faces challenges with absent control samples and potential cancer cell polyploidy.
- Accurate copy number alteration (CNA) detection is crucial for understanding cancer development and progression.
Purpose of the Study:
- To present FREEC (control-FREE Copy number caller), a novel tool for CNA detection in deep-sequencing data.
- To provide a solution for analyzing cancer sequencing data without control samples and accounting for polyploidy.
Main Methods:
- FREEC automatically normalizes and segments copy number profiles (CNPs) from deep-sequencing data.
- Normalization can utilize available control datasets or GC content, particularly effective for Illumina sequencing data.
- The tool calls CNAs and assigns absolute copy numbers when ploidy information is provided.
Main Results:
- GC-content normalization yields smooth CNPs suitable for segmentation and CNA prediction.
- FREEC effectively handles the absence of control samples and potential polyploidy in cancer data.
- Demonstrated utility for single-end, mate-pair, and paired-end sequencing data.
Conclusions:
- FREEC offers a robust method for control-free CNA detection in cancer genomics.
- The tool simplifies and enhances the analysis of complex cancer sequencing data.
- FREEC is particularly valuable for cancer studies requiring precise copy number profiling.
Related Concept Videos
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%...
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%...
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.
Next-generation Sequencing
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.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
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,...
RNA-seq
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
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