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Updated: Jun 4, 2026
09:45
Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
A novel approach to DNA copy number data segmentation.
Siling Wang1, Yuhang Wang, Yang Xie
1Department of Computer Science and Engineering, Southern Methodist University, Dallas, Texas 75205, USA. silingw@smu.edu
Journal of Bioinformatics and Computational Biology
|February 18, 2011
Summary
This study introduces a new computational method for analyzing DNA copy number (DCN) data from tumor samples. The method accurately segments DCN changes and estimates tumor purity, outperforming existing approaches.
Area of Science:
- Genomics
- Computational Biology
- Cancer Research
Background:
- DNA copy number (DCN) alterations are crucial in tumor development.
- Microarray technologies detect DCN changes but yield noisy data, often mixed with normal cells.
- Existing computational methods struggle to explicitly model tumor/normal cell mixtures and segment DCN data.
Purpose of the Study:
- To develop a novel model-based method for accurate DNA copy number data segmentation.
- To infer underlying DCNs and simultaneously estimate tumor proportion from noisy microarray data.
- To improve upon existing DCN analysis techniques.
Main Methods:
- Developed a novel model-based method utilizing the minimum description length (MDL) principle.
- Applied the method to segment chromosomal regions and annotate DCN.
- Inferred the underlying tumor proportion within samples.
Main Results:
- The new method successfully outputs DCN for chromosomal segments.
- It accurately infers the tumor proportion in test samples.
- Empirical results demonstrate superior accuracy compared to Circular Binary Segmentation, Hidden Markov Model, and Ultrasome.
Conclusions:
- The developed MDL-based method provides accurate DCN segmentation and tumor proportion inference.
- This approach offers significant improvements over previous DCN analysis methods.
- It enhances the computational analysis of array-based DCN data in cancer research.
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%...
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Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
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01:57Sanger Sequencing
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