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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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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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Genome Copying Errors02:46

Genome Copying Errors

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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.
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Gene Duplication and Divergence02:37

Gene Duplication and Divergence

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The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
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...
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Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
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Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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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,...
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DNA Microarrays02:34

DNA Microarrays

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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Updated: Jun 27, 2025

Detection of Copy Number Alterations Using Single Cell Sequencing
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Detection of Copy Number Alterations Using Single Cell Sequencing

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CopyVAE: a variational autoencoder-based approach for copy number variation inference using single-cell

Semih Kurt1, Mandi Chen1, Hosein Toosi1

  • 1School of EECS and SciLifeLab, KTH Royal Institute of Technology, Stockholm, 100 44, Sweden.

Bioinformatics (Oxford, England)
|April 27, 2024
PubMed
Summary
This summary is machine-generated.

Copy number variations (CNVs) are common in tumors. CopyVAE, a new deep learning tool, accurately detects CNVs from single-cell RNA sequencing data, improving upon existing methods.

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Area of Science:

  • Genomics
  • Computational Biology
  • Cancer Research

Background:

  • Copy number variations (CNVs) are frequent genetic alterations in cancer cells.
  • Understanding CNVs is crucial for cancer progression insights and unraveling intratumoral heterogeneity.
  • Accurate CNV inference from single-cell sequencing data is vital but challenging due to resolution and sensitivity limits of current methods.

Purpose of the Study:

  • To introduce CopyVAE, a novel deep learning framework for CNV detection.
  • To address limitations in resolution and sensitivity of existing CNV inference methods.
  • To leverage variational autoencoder architecture for enhanced CNV analysis.

Main Methods:

  • Development of CopyVAE, a deep learning framework utilizing a variational autoencoder.
  • Application of CopyVAE to single-cell RNA sequencing data.
  • Comparative analysis against existing CNV inference methods.

Main Results:

  • CopyVAE demonstrates accurate and reliable detection of CNVs from single-cell RNA sequencing data.
  • CopyVAE exhibits superior sensitivity and specificity compared to existing methods.
  • The framework successfully addresses challenges in CNV inference resolution and sensitivity.

Conclusions:

  • CopyVAE offers a significant advancement in CNV detection from single-cell data.
  • The tool has the potential to deepen the understanding of genetic alterations in cancer.
  • CopyVAE can contribute to a better understanding of disease progression and genetic impacts.