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Updated: Jun 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

CNV-ECOD: A copy number variation detection method based on ECOD algorithm using next-generation sequencing data.

Ranran Sun¹, Jinxin Dong¹, Hua Jiang¹

¹Department of Software Engineering, School of Computer Science and Technology, Liaocheng University, Liaocheng 252000, P. R. China.

Journal of Bioinformatics and Computational Biology

|June 22, 2026

Summary

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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

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.

Single Nucleotide Polymorphisms-SNPs

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,...

Sanger Sequencing

Sanger Sequencing

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...

RNA-seq

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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This summary is machine-generated.

CNV-ECOD accurately detects copy number variations (CNVs) using read depth, paired-end mapping, and split reads. This method improves precision and sensitivity for genetic disease analysis.

Area of Science:

Genomics
Bioinformatics
Human Genetics

Background:

Copy number variations (CNVs) are significant DNA structural variations (SVs) implicated in human diseases and genetic diversity.
Accurate CNV identification is crucial for disease mechanism analysis, personalized medicine, and drug development.
Existing next-generation sequencing (NGS) based CNV detection methods often suffer from high false positives and imprecise boundaries.

Purpose of the Study:

To propose a novel, accurate, and robust method for detecting CNVs from single-sample NGS data.
To address limitations of current CNV detection tools, specifically false positives and boundary inaccuracies.
To enhance the reliability of CNV detection for downstream applications in clinical genetics and research.

Main Methods:

Keywords:

Copy number variation empirical-cumulative-distribution-based outlier detection algorithm next-generation sequencing technology paired-end mapping read depth split read

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Last Updated: Jun 23, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing

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Published on: February 17, 2017

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Developed CNV-ECOD, a method integrating empirical-cumulative-distribution-based outlier detection (ECOD) for read depth (RD) signal analysis.
Incorporated paired-end mapping (PEM) and split read (SR) strategies to refine CNV detection and correct false positives.
Utilized a hierarchical progressive framework combining RD, PEM, and SR with an ECOD-based anomaly scoring mechanism.

Main Results:

CNV-ECOD demonstrated superior performance compared to four existing methods in simulation experiments, achieving an optimal balance between precision and sensitivity.
The method achieved the highest F1-scores and overlap density scores (ODSs) in real-sample experiments.
Results indicate significant improvements in accuracy and robustness for CNV detection.

Conclusions:

CNV-ECOD offers an effective solution for accurate CNV detection from NGS data.
The integrated RD-PEM-SR framework with ECOD enhances CNV identification accuracy and boundary refinement.
CNV-ECOD is poised to become a valuable tool for genetic variation analysis in research and clinical settings.