Evidence map›Paper›PMID 26865945›Full record

ReviewJournal of biomedical semantics2016

Reporting phenotypes in mouse models when considering body size as a potential confounder.

Anika Oellrich, Terrence F Meehan, Helen Parkinson, Sirarat Sarntivijai, Jacqueline K White, Natasha A Karp

Abstract readReview
In one paragraph

Review in Journal of biomedical semantics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. A comprehensive and comparative phenotypic analysis of the collaborative founder strains identifies new and known phenotypes.Mammalian genome : official journal of the International Mammalian Genome Society · 2020
    Article
  5. Article
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Anika OellrichMouse Informatics Group, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire UK ; Social Genetic & Developmental Psychiatry, King's College London, London, UK.
Terrence F MeehanSamples, Phenotypes and Ontologies, European Molecular Biology Laboratory-European Bioinformatics Institute, Hinxton, Cambridge UK.
Helen ParkinsonSamples, Phenotypes and Ontologies, European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK.
Sirarat SarntivijaiSamples, Phenotypes and Ontologies, European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK ; The Centre for Therapeutic Target Validation, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK.
Jacqueline K WhiteMouse Genetics Project, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire UK.
Natasha A KarpMouse Informatics Group, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire UK.ORCID 0000-0002-8404-2907

Funding

Mouse Phenotyping Informatics Infrastruture - MP12U54HG006370 · NHGRI · EUROPEAN MOLECULAR BIOLOGY LABORATORY · PI BROWN, STEVE, FLICEK, PAUL · 2011 to 2015
$11.4M
NHGRI NIH HHS 1 U54 HG006370-01NHGRI NIH HHS U54 HG006370Wellcome TrustWellcome Trust WT098051
6 · The paper itself

Abstract

Genotype-phenotype studies aim to identify causative relationships between genes and phenotypes. The International Mouse Phenotyping Consortium is a high throughput phenotyping program whose goal is to collect phenotype data for a knockout mouse strain of every protein coding gene. The scale of the project requires an automatic analysis pipeline to detect abnormal phenotypes, and disseminate the resulting gene-phenotype annotation data into public resources. A body weight phenotype is a common result of knockout studies. As body weight correlates with many other biological traits, this challenges the interpretation of related gene-phenotype associations. Co-correlation can lead to gene-phenotype associations that are potentially misleading. Here we use statistical modelling to account for body weight as a potential confounder to assess the impact. We find that there is a considerable impact on previously established gene-phenotype associations due to an increase in sensitivity as well as the confounding effect. We investigated the existing ontologies to represent this phenotypic information and we explored ways to ontologically represent the results of the influence of confounders on gene-phenotype associations. With the scale of data being disseminated within the high throughput programs and the range of downstream studies that utilise these data, it is critical to consider how we improve the quality of the disseminated data and provide a robust ontological representation.

Indexed as

Body SizeGene OntologyPhenotypeAnimalsFemaleGenotypeMaleMiceModels, AnimalReference Standards

Identifiers

PMID26865945
PMCPMC4748495

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.