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Visual annotation display (VLAD): a tool for finding functional themes in lists of genes

Overview of attention for article published in Mammalian Genome, June 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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1 blog
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1 X user
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1 Facebook page

Citations

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36 Dimensions

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32 Mendeley
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1 CiteULike
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Title
Visual annotation display (VLAD): a tool for finding functional themes in lists of genes
Published in
Mammalian Genome, June 2015
DOI 10.1007/s00335-015-9570-2
Pubmed ID
Authors

Joel E. Richardson, Carol J. Bult

Abstract

Experiments that employ genome scale technology platforms frequently result in lists of tens to thousands of genes with potential significance to a specific biological process or disease. Searching for biologically relevant connections among the genes or gene products in these lists is a common data analysis task. We have implemented a software application for uncovering functional themes in sets of genes based on their annotations to bio-ontologies, such as the gene ontology and the mammalian phenotype ontology. The application, called VisuaL Annotation Display (VLAD), performs a statistical analysis to test for the enrichment of ontology terms in a set of genes submitted by a researcher. The results for each analysis using VLAD includes a table of ontology terms, sorted in decreasing order of significance. Each row contains the term, statistics such as the number of annotated terms, the p value, etc., and the symbols of annotated genes. An accompanying graphical display shows portions of the ontology hierarchy, where node sizes are scaled based on p values. Although numerous ontology term enrichment programs already exist, VLAD is unique in that it allows users to upload their own annotation files and ontologies for customized term enrichment analyses, supports the analysis of multiple gene sets at once, provides interfaces to customize graphical output, and is tightly integrated with functional and biological details about mouse genes in the Mouse Genome Informatics (MGI) database. VLAD is available as a web-based application from the MGI web site ( http://proto.informatics.jax.org/prototypes/vlad/ ).

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Uruguay 1 3%
Unknown 31 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 19%
Student > Ph. D. Student 5 16%
Student > Master 4 13%
Student > Bachelor 2 6%
Student > Postgraduate 2 6%
Other 4 13%
Unknown 9 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 19%
Biochemistry, Genetics and Molecular Biology 5 16%
Social Sciences 4 13%
Medicine and Dentistry 3 9%
Computer Science 1 3%
Other 2 6%
Unknown 11 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 June 2015.
All research outputs
#2,910,597
of 22,813,792 outputs
Outputs from Mammalian Genome
#51
of 1,126 outputs
Outputs of similar age
#39,436
of 266,604 outputs
Outputs of similar age from Mammalian Genome
#3
of 18 outputs
Altmetric has tracked 22,813,792 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,126 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,604 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.