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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

11.6K
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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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...
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Related Experiment Video

Updated: May 2, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
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Published on: October 18, 2013

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Comparative analysis of methods for identifying somatic copy number alterations from deep sequencing data.

Amjad Alkodsi, Riku Louhimo, Sampsa Hautaniemi

    Briefings in Bioinformatics
    |March 7, 2014
    PubMed
    Summary

    This study compares ten algorithms for detecting somatic copy-number alterations (SCNAs) in cancer genomics. Results show significant performance differences and confirm exome sequencing

    Keywords:
    Somatic copy number alterationsalgorithm comparisoncancerwhole-exome sequencingwhole-genome sequencing

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    Last Updated: May 2, 2026

    Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
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    Area of Science:

    • Genomics
    • Cancer Biology
    • Bioinformatics

    Background:

    • Somatic copy-number alterations (SCNAs) are key structural variations in tumor pathogenesis.
    • Identifying SCNA regions is vital for pinpointing cancer drivers.
    • Deep sequencing offers high-resolution data for SCNA detection.

    Purpose of the Study:

    • To compare the performance of ten SCNA detection algorithms.
    • To evaluate the utility of exome sequencing for SCNA detection.

    Main Methods:

    • Comparison of ten SCNA detection algorithms.
    • Utilized simulated and primary tumor deep sequencing data.
    • Assessed exome sequencing data for SCNA detection.

    Main Results:

    • Significant differences in sensitivity and specificity were observed among algorithms.
    • SCNA detection algorithms successfully identified most complex chromosomal alterations.
    • Exome sequencing data proved suitable for SCNA detection.

    Conclusions:

    • Algorithm choice impacts SCNA detection accuracy.
    • Deep and exome sequencing are valuable for SCNA analysis in cancer genomics.