Robust and sensitive analysis of mouse knockout phenotypes.

A significant challenge of in-vivo studies is the identification of phenotypes with a method that is robust and reliable. The challenge arises from practical issues that lead to experimental designs which are not ideal. Breeding issues, particularly in the presence of fertility or fecundity problems...

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Autores principales:	Natasha A Karp, David Melvin, Sanger Mouse Genetics Project, Richard F Mott
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2932fb5980634f9490cd10fcf47d8740
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spelling	oai:doaj.org-article:2932fb5980634f9490cd10fcf47d87402021-11-18T08:03:42ZRobust and sensitive analysis of mouse knockout phenotypes.1932-620310.1371/journal.pone.0052410https://doaj.org/article/2932fb5980634f9490cd10fcf47d87402012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23300663/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203A significant challenge of in-vivo studies is the identification of phenotypes with a method that is robust and reliable. The challenge arises from practical issues that lead to experimental designs which are not ideal. Breeding issues, particularly in the presence of fertility or fecundity problems, frequently lead to data being collected in multiple batches. This problem is acute in high throughput phenotyping programs. In addition, in a high throughput environment operational issues lead to controls not being measured on the same day as knockouts. We highlight how application of traditional methods, such as a Student's t-Test or a 2-way ANOVA, in these situations give flawed results and should not be used. We explore the use of mixed models using worked examples from Sanger Mouse Genome Project focusing on Dual-Energy X-Ray Absorptiometry data for the analysis of mouse knockout data and compare to a reference range approach. We show that mixed model analysis is more sensitive and less prone to artefacts allowing the discovery of subtle quantitative phenotypes essential for correlating a gene's function to human disease. We demonstrate how a mixed model approach has the additional advantage of being able to include covariates, such as body weight, to separate effect of genotype from these covariates. This is a particular issue in knockout studies, where body weight is a common phenotype and will enhance the precision of assigning phenotypes and the subsequent selection of lines for secondary phenotyping. The use of mixed models with in-vivo studies has value not only in improving the quality and sensitivity of the data analysis but also ethically as a method suitable for small batches which reduces the breeding burden of a colony. This will reduce the use of animals, increase throughput, and decrease cost whilst improving the quality and depth of knowledge gained.Natasha A KarpDavid MelvinSanger Mouse Genetics ProjectRichard F MottPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 12, p e52410 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Natasha A Karp David Melvin Sanger Mouse Genetics Project Richard F Mott Robust and sensitive analysis of mouse knockout phenotypes.
description	A significant challenge of in-vivo studies is the identification of phenotypes with a method that is robust and reliable. The challenge arises from practical issues that lead to experimental designs which are not ideal. Breeding issues, particularly in the presence of fertility or fecundity problems, frequently lead to data being collected in multiple batches. This problem is acute in high throughput phenotyping programs. In addition, in a high throughput environment operational issues lead to controls not being measured on the same day as knockouts. We highlight how application of traditional methods, such as a Student's t-Test or a 2-way ANOVA, in these situations give flawed results and should not be used. We explore the use of mixed models using worked examples from Sanger Mouse Genome Project focusing on Dual-Energy X-Ray Absorptiometry data for the analysis of mouse knockout data and compare to a reference range approach. We show that mixed model analysis is more sensitive and less prone to artefacts allowing the discovery of subtle quantitative phenotypes essential for correlating a gene's function to human disease. We demonstrate how a mixed model approach has the additional advantage of being able to include covariates, such as body weight, to separate effect of genotype from these covariates. This is a particular issue in knockout studies, where body weight is a common phenotype and will enhance the precision of assigning phenotypes and the subsequent selection of lines for secondary phenotyping. The use of mixed models with in-vivo studies has value not only in improving the quality and sensitivity of the data analysis but also ethically as a method suitable for small batches which reduces the breeding burden of a colony. This will reduce the use of animals, increase throughput, and decrease cost whilst improving the quality and depth of knowledge gained.
format	article
author	Natasha A Karp David Melvin Sanger Mouse Genetics Project Richard F Mott
author_facet	Natasha A Karp David Melvin Sanger Mouse Genetics Project Richard F Mott
author_sort	Natasha A Karp
title	Robust and sensitive analysis of mouse knockout phenotypes.
title_short	Robust and sensitive analysis of mouse knockout phenotypes.
title_full	Robust and sensitive analysis of mouse knockout phenotypes.
title_fullStr	Robust and sensitive analysis of mouse knockout phenotypes.
title_full_unstemmed	Robust and sensitive analysis of mouse knockout phenotypes.
title_sort	robust and sensitive analysis of mouse knockout phenotypes.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/2932fb5980634f9490cd10fcf47d8740
work_keys_str_mv	AT natashaakarp robustandsensitiveanalysisofmouseknockoutphenotypes AT davidmelvin robustandsensitiveanalysisofmouseknockoutphenotypes AT sangermousegeneticsproject robustandsensitiveanalysisofmouseknockoutphenotypes AT richardfmott robustandsensitiveanalysisofmouseknockoutphenotypes
_version_	1718422469329551360

Robust and sensitive analysis of mouse knockout phenotypes.

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