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Related Concept Videos

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.
Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...

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Related Experiment Video

Updated: May 15, 2026

Using Mouse Oocytes to Assess Human Gene Function During Meiosis I
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Published on: April 10, 2018

Robust and sensitive analysis of mouse knockout phenotypes.

Natasha A Karp1, David Melvin,

  • 1Mouse Informatics Group, Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom. nk3@sanger.ac.uk

Plos One
|January 10, 2013
PubMed
Summary
This summary is machine-generated.

Mixed models offer a robust solution for analyzing in-vivo study data, overcoming challenges in high-throughput phenotyping and improving the discovery of subtle quantitative phenotypes. This approach enhances data sensitivity and ethical considerations in animal research.

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Last Updated: May 15, 2026

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Published on: April 10, 2018

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Area of Science:

  • Genomics
  • Animal Models
  • Statistical Genetics

Background:

  • In-vivo studies face challenges in reliable phenotype identification due to experimental design limitations.
  • High-throughput phenotyping programs are particularly affected by batch effects from breeding issues and operational constraints.
  • Traditional statistical methods like Student's t-Test and 2-way ANOVA yield flawed results in these complex experimental designs.

Purpose of the Study:

  • To evaluate the efficacy of mixed models for analyzing in-vivo mouse knockout data, specifically Dual-Energy X-Ray Absorptiometry (DXA) data.
  • To compare the performance of mixed models against traditional methods and a reference range approach.
  • To demonstrate the advantages of mixed models in identifying subtle quantitative phenotypes and handling covariates.

Main Methods:

  • Application of mixed models to analyze mouse knockout data from the Sanger Mouse Genome Project.
  • Utilized Dual-Energy X-Ray Absorptiometry (DXA) data for analysis.
  • Compared mixed model results with traditional statistical tests (Student's t-Test, 2-way ANOVA) and a reference range approach.

Main Results:

  • Mixed model analysis proved more sensitive and less prone to artifacts compared to traditional methods.
  • The approach successfully identified subtle quantitative phenotypes crucial for gene function correlation.
  • Mixed models effectively incorporated covariates like body weight, enhancing the precision of genotype-effect separation.

Conclusions:

  • Mixed models provide a superior analytical framework for in-vivo studies, particularly in high-throughput phenotyping.
  • This method improves data quality, sensitivity, and the discovery of biologically relevant phenotypes.
  • The use of mixed models offers ethical benefits by reducing animal usage and costs through efficient analysis of smaller batches.