↓ Skip to main content

clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters

Overview of attention for article published in OMICS: A Journal of Integrative Biology, May 2012
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#21 of 441)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

blogs
2 blogs
twitter
19 tweeters
patent
1 patent
weibo
1 weibo user
wikipedia
1 Wikipedia page

Citations

dimensions_citation
2005 Dimensions

Readers on

mendeley
1196 Mendeley
citeulike
2 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
Published in
OMICS: A Journal of Integrative Biology, May 2012
DOI 10.1089/omi.2011.0118
Pubmed ID
Authors

Guangchuang Yu, Li-Gen Wang, Yanyan Han, Qing-Yu He

Abstract

Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.

Twitter Demographics

The data shown below were collected from the profiles of 19 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 1,196 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 <1%
United Kingdom 3 <1%
Spain 3 <1%
Brazil 2 <1%
Portugal 1 <1%
Italy 1 <1%
Australia 1 <1%
Korea, Republic of 1 <1%
Sweden 1 <1%
Other 10 <1%
Unknown 1169 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 309 26%
Researcher 216 18%
Student > Master 159 13%
Student > Bachelor 117 10%
Student > Doctoral Student 69 6%
Other 169 14%
Unknown 157 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 388 32%
Biochemistry, Genetics and Molecular Biology 364 30%
Medicine and Dentistry 77 6%
Computer Science 40 3%
Immunology and Microbiology 28 2%
Other 104 9%
Unknown 195 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 34. 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 04 February 2020.
All research outputs
#553,517
of 14,282,317 outputs
Outputs from OMICS: A Journal of Integrative Biology
#21
of 441 outputs
Outputs of similar age
#3,788
of 122,236 outputs
Outputs of similar age from OMICS: A Journal of Integrative Biology
#1
of 8 outputs
Altmetric has tracked 14,282,317 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 441 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. 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 122,236 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them