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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

11.4K
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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Related Experiment Video

Updated: Apr 23, 2026

Comparative Lesions Analysis Through a Targeted Sequencing Approach
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Published on: November 5, 2019

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A general framework for analyzing tumor subclonality using SNP array and DNA sequencing data.

Bo Li, Jun Z Li

    Genome Biology
    |September 26, 2014
    PubMed
    Summary
    This summary is machine-generated.

    Cancer evolution involves intra-tumor heterogeneity, complicating analysis of somatic copy number alterations (sCNA) and mutations. A new tool estimates cellular fractions for both, revealing multiple aneuploid clones in over half of breast tumors analyzed.

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    Related Experiment Videos

    Last Updated: Apr 23, 2026

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    Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
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    Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
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    Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

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    Area of Science:

    • Oncology
    • Genomics
    • Bioinformatics

    Background:

    • Intra-tumor heterogeneity is crucial for understanding cancer evolution, diagnosis, and treatment.
    • Analyzing somatic copy number alterations (sCNA) and point mutations in bulk tumor tissues presents challenges in estimating cellular fractions, especially when mutations overlap with sCNAs.

    Purpose of the Study:

    • To develop and present a computational tool for estimating cellular fractions of both sCNAs and mutations.
    • To utilize these estimations to infer the macroscopic clonal architecture within tumors.

    Main Methods:

    • Development of the Clonal Heterogeneity Analysis Tool.
    • Application of the tool to profile approximately 700 breast tumors.
    • Analysis of distributions of estimated cellular fractions for sCNAs and mutations.

    Main Results:

    • The Clonal Heterogeneity Analysis Tool successfully estimates cellular fractions for both sCNAs and mutations.
    • Over half of the analyzed breast tumors exhibited multiple distinct aneuploid tumor clones.
    • Significant subtype-specific variations in the clonality of known cancer genes were observed.

    Conclusions:

    • The developed tool effectively deconvolutes tumor heterogeneity by estimating cellular fractions of genetic alterations.
    • The findings reveal a high prevalence of multi-clonal aneuploidy in breast cancer.
    • Clonality patterns differ across breast cancer subtypes, offering insights into distinct evolutionary trajectories.