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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

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%...
Genome Copying Errors02:46

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.
DNA Microarrays02:34

DNA Microarrays

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...
Single Nucleotide Polymorphisms-SNPs01:05

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,...
Gene Duplication and Divergence02:37

Gene Duplication and Divergence

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 characterized.

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Related Experiment Video

Updated: Jul 12, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

SPICE: A Robust Computational Framework for Identifying Copy Number Variations in Spatial Transcriptomics.

Kalins Banerjee, Robert C Langefeld, Evan T Keller

    Biorxiv : the Preprint Server for Biology
    |July 10, 2026
    PubMed
    Summary

    SPICE is a new method that analyzes spatial transcriptomics data to identify copy number variations (CNVs) in tumors. This approach helps map cancer subclone organization and genomic heterogeneity within tissues.

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    Last Updated: Jul 12, 2026

    Detection of Copy Number Alterations Using Single Cell Sequencing
    09:45

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    Published on: February 17, 2017

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    Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
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    Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

    Published on: December 9, 2016

    Area of Science:

    • Genomics
    • Cancer Biology
    • Bioinformatics

    Background:

    • Intratumor heterogeneity, driven by copy number variation (CNV), creates distinct cancer cell populations.
    • Spatially resolved transcriptomic (SRT) technologies enable gene expression profiling across tissue locations, offering potential for CNV reconstruction.

    Purpose of the Study:

    • To introduce SPICE, a probabilistic method for identifying somatic CNVs and allele-specific copy number (ASCN) profiles from SRT data.
    • To enhance the accuracy and power of CNV detection by integrating multiple data types from SRT.

    Main Methods:

    • SPICE integrates gene expression, spatial coordinates, and heterozygous single nucleotide polymorphisms (SNPs) inferred from transcriptomic reads.
    • The method's reliability was assessed using SNP data from various SRT platforms.

    Main Results:

    • SPICE accurately reconstructs CNV landscapes and subclonal architecture with spatial coherence.
    • The method demonstrates effective integration of multiple data modalities for robust CNV inference.
    • SPICE maintains excellent control over false discoveries in CNV detection.

    Conclusions:

    • SPICE offers a robust solution for dissecting genomic heterogeneity in cancer using SRT data.
    • The method facilitates a deeper understanding of the spatial organization of cancer subclones.