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PhenStat: A Tool Kit for Standardized Analysis of High Throughput Phenotypic Data.

Kurbatova N, Mason JC, Morgan H, Meehan TF, Karp NA - PLoS ONE (2015)

Bottom Line: PhenStat is targeted to two user groups: small-scale users who wish to interact and test data from large resources and large-scale users who require an automated statistical analysis pipeline.The package was tested on mouse and rat data and is used by the International Mouse Phenotyping Consortium (IMPC).By providing raw data and the version of PhenStat used, resources like the IMPC give users the ability to replicate and explore results within their own computing environment.

View Article: PubMed Central - PubMed

Affiliation: The EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom.

ABSTRACT
The lack of reproducibility with animal phenotyping experiments is a growing concern among the biomedical community. One contributing factor is the inadequate description of statistical analysis methods that prevents researchers from replicating results even when the original data are provided. Here we present PhenStat--a freely available R package that provides a variety of statistical methods for the identification of phenotypic associations. The methods have been developed for high throughput phenotyping pipelines implemented across various experimental designs with an emphasis on managing temporal variation. PhenStat is targeted to two user groups: small-scale users who wish to interact and test data from large resources and large-scale users who require an automated statistical analysis pipeline. The software provides guidance to the user for selecting appropriate analysis methods based on the dataset and is designed to allow for additions and modifications as needed. The package was tested on mouse and rat data and is used by the International Mouse Phenotyping Consortium (IMPC). By providing raw data and the version of PhenStat used, resources like the IMPC give users the ability to replicate and explore results within their own computing environment.

No MeSH data available.


The Reference Range Plus method.a) Determining the thresholds for classifying the measures as low, normal or high based on the natural variation seen in the control data. b) Formation of a 2x2 count table following the classification of the measured animals. c) The observed proportions seen in tables (b) are compared with a Fisher Exact Test and effect quantified by calculating a change in penetrance in classification.
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pone.0131274.g004: The Reference Range Plus method.a) Determining the thresholds for classifying the measures as low, normal or high based on the natural variation seen in the control data. b) Formation of a 2x2 count table following the classification of the measured animals. c) The observed proportions seen in tables (b) are compared with a Fisher Exact Test and effect quantified by calculating a change in penetrance in classification.

Mentions: The "Reference Range Plus" (RR) method is an intuitive, simple, conservative method based on the concept that a significant phenotype can be called when the majority of animals lie outside the natural variation seen in the control animals within particular institute. A similar concept was used in the large scale study of knockout data from the Wellcome Trust Sanger Institute Mouse Genetics Project [15] and the ENU-mutagenesis project [22]. It is also comparable to medical investigations for humans where measurements are compared to baseline readings. Our implementation is based on classifying the analysable variable values as high, normal, low based on the natural variation seen within the control data and comparing the proportions seen with a Fisher Exact Test (Fig 4).


PhenStat: A Tool Kit for Standardized Analysis of High Throughput Phenotypic Data.

Kurbatova N, Mason JC, Morgan H, Meehan TF, Karp NA - PLoS ONE (2015)

The Reference Range Plus method.a) Determining the thresholds for classifying the measures as low, normal or high based on the natural variation seen in the control data. b) Formation of a 2x2 count table following the classification of the measured animals. c) The observed proportions seen in tables (b) are compared with a Fisher Exact Test and effect quantified by calculating a change in penetrance in classification.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493137&req=5

pone.0131274.g004: The Reference Range Plus method.a) Determining the thresholds for classifying the measures as low, normal or high based on the natural variation seen in the control data. b) Formation of a 2x2 count table following the classification of the measured animals. c) The observed proportions seen in tables (b) are compared with a Fisher Exact Test and effect quantified by calculating a change in penetrance in classification.
Mentions: The "Reference Range Plus" (RR) method is an intuitive, simple, conservative method based on the concept that a significant phenotype can be called when the majority of animals lie outside the natural variation seen in the control animals within particular institute. A similar concept was used in the large scale study of knockout data from the Wellcome Trust Sanger Institute Mouse Genetics Project [15] and the ENU-mutagenesis project [22]. It is also comparable to medical investigations for humans where measurements are compared to baseline readings. Our implementation is based on classifying the analysable variable values as high, normal, low based on the natural variation seen within the control data and comparing the proportions seen with a Fisher Exact Test (Fig 4).

Bottom Line: PhenStat is targeted to two user groups: small-scale users who wish to interact and test data from large resources and large-scale users who require an automated statistical analysis pipeline.The package was tested on mouse and rat data and is used by the International Mouse Phenotyping Consortium (IMPC).By providing raw data and the version of PhenStat used, resources like the IMPC give users the ability to replicate and explore results within their own computing environment.

View Article: PubMed Central - PubMed

Affiliation: The EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom.

ABSTRACT
The lack of reproducibility with animal phenotyping experiments is a growing concern among the biomedical community. One contributing factor is the inadequate description of statistical analysis methods that prevents researchers from replicating results even when the original data are provided. Here we present PhenStat--a freely available R package that provides a variety of statistical methods for the identification of phenotypic associations. The methods have been developed for high throughput phenotyping pipelines implemented across various experimental designs with an emphasis on managing temporal variation. PhenStat is targeted to two user groups: small-scale users who wish to interact and test data from large resources and large-scale users who require an automated statistical analysis pipeline. The software provides guidance to the user for selecting appropriate analysis methods based on the dataset and is designed to allow for additions and modifications as needed. The package was tested on mouse and rat data and is used by the International Mouse Phenotyping Consortium (IMPC). By providing raw data and the version of PhenStat used, resources like the IMPC give users the ability to replicate and explore results within their own computing environment.

No MeSH data available.