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Related Concept Videos

Cancer02:18

Cancer

Cancers arise due to mutations in genes involved in the regulation of cell division, which leads to unrestricted cell proliferation. Modern science and medicine have made great strides in the understanding and treatment of cancer, including eradicating cancer in some patients. However, there is still no cure for cancer. This is largely due to the fact that cancer is a large group of many diseases.
Mutations01:39

Mutations

Overview
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%...
In vitro Mutagenesis01:16

In vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.
Cancer-Critical Genes II: Tumor Suppressor Genes01:05

Cancer-Critical Genes II: Tumor Suppressor Genes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
Genetic Variation01:25

Genetic Variation

Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles, which...

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Related Experiment Video

Updated: May 14, 2026

Simple and Rapid Method to Obtain High-quality Tumor DNA from Clinical-pathological Specimens Using Touch Imprint Cytology
11:20

Simple and Rapid Method to Obtain High-quality Tumor DNA from Clinical-pathological Specimens Using Touch Imprint Cytology

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Tutorial for variant interrogation in tumor samples.

Riley J Arseneau1,2, Leah K MacLean1,2, Jeanette E Boudreau1,2,3

  • 1Department of Pathology, Dalhousie University, Halifax, Nova Scotia, Canada.

Plos Computational Biology
|February 17, 2026
PubMed
Summary
This summary is machine-generated.

This framework simplifies cancer somatic variant analysis using next-generation sequencing. It guides researchers through planning, resource gathering, filtering, and dissemination for reproducible and clinically relevant findings.

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Related Experiment Videos

Last Updated: May 14, 2026

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Area of Science:

  • Genomics
  • Cancer Research
  • Bioinformatics

Background:

  • Next-generation sequencing (NGS) enables somatic mutation detection in cancer.
  • Variant analysis pipelines present significant barriers due to complexity and tool selection.
  • Researchers, especially in translational settings, need accessible guidance.

Purpose of the Study:

  • To provide a practical framework for navigating somatic variant interrogation in tumor samples.
  • To address the complexity and accessibility challenges in cancer variant analysis.
  • To enhance confidence and rigor in analyzing tumor sequencing data.

Main Methods:

  • A four-phase framework: Planning, Gathering Resources, Filtering and Validation, Dissemination and Storage.
  • Emphasis on experimental design, tool assembly, variant prioritization, and data sharing.
  • Focus on accessibility, reproducibility, and clinical relevance.

Main Results:

  • A structured approach to guide researchers through critical steps of variant analysis.
  • Facilitates understanding of sequencing outputs and selection of necessary resources.
  • Enables systematic filtering and validation for meaningful variant identification.

Conclusions:

  • The framework empowers researchers to confidently perform somatic variant analysis.
  • Promotes reproducible and clinically relevant cancer research through transparent reporting and data sharing.
  • Aids in overcoming barriers in variant analysis for diverse research settings.