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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Genetic Variation01:25

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Related Experiment Video

Updated: May 10, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
11:02

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Published on: October 18, 2013

Joint genotype inference with germline and somatic mutations.

Eric Bareke1, Virginie Saillour, Jean-François Spinella

  • 1Department of Computer Science and Operations Research, University of Montréal, QC, Canada.

BMC Bioinformatics
|June 6, 2013
PubMed
Summary

Joint genome sequencing of families helps find rare genetic variants. This study developed a new method for analyzing childhood acute lymphoblastic leukemia (ALL) quartet data to uncover genetic alterations.

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Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
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Last Updated: May 10, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
11:02

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Published on: October 18, 2013

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

Area of Science:

  • Genomics
  • Cancer Genetics
  • Bioinformatics

Background:

  • Joint sequencing of related genomes aids rare variant discovery.
  • Normal-tumor pairs identify somatic mutations in cancers.
  • Parental/sibling genomes reveal germline mutations and inheritance patterns.

Purpose of the Study:

  • To uncover germline and somatic genetic alterations in childhood acute lymphoblastic leukemia (ALL).
  • To develop a general probabilistic model for quartet sequencing data analysis.
  • To implement an open-source software package for genotype inference.

Main Methods:

  • Whole-exome re-sequencing of over 120 childhood ALL quartets (patient tumor, matched-normal, and both parents).
  • Development of a probabilistic model for joint genotype inference across quartet genomes.
  • Implementation of algorithms and data structures in the open-source software package QUADGT.

Main Results:

  • A novel probabilistic model and software (QUADGT) were developed for analyzing quartet sequencing data.
  • The method enables joint genotype inference at homologous loci across normal-tumor pairs and parental genomes.
  • The utility of the method was demonstrated on childhood ALL quartet data.

Conclusions:

  • The developed method and software provide a powerful tool for analyzing complex family-based sequencing data.
  • This approach facilitates the discovery of both germline and somatic genetic alterations in diseases like ALL.
  • The open-source nature of QUADGT promotes broader application in genetic research.