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Gene ontology analysis for RNA-seq: accounting for selection bias

Overview of attention for article published in Genome Biology, February 2010
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
74 X users
patent
2 patents
wikipedia
3 Wikipedia pages
googleplus
1 Google+ user
q&a
1 Q&A thread

Citations

dimensions_citation
5321 Dimensions

Readers on

mendeley
2490 Mendeley
citeulike
42 CiteULike
connotea
3 Connotea
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Title
Gene ontology analysis for RNA-seq: accounting for selection bias
Published in
Genome Biology, February 2010
DOI 10.1186/gb-2010-11-2-r14
Pubmed ID
Authors

Matthew D Young, Matthew J Wakefield, Gordon K Smyth, Alicia Oshlack

Abstract

We present GOseq, an application for performing Gene Ontology (GO) analysis on RNA-seq data. GO analysis is widely used to reduce complexity and highlight biological processes in genome-wide expression studies, but standard methods give biased results on RNA-seq data due to over-detection of differential expression for long and highly expressed transcripts. Application of GOseq to a prostate cancer data set shows that GOseq dramatically changes the results, highlighting categories more consistent with the known biology.

X Demographics

X Demographics

The data shown below were collected from the profiles of 74 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2,490 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 49 2%
United Kingdom 13 <1%
Germany 11 <1%
Italy 8 <1%
Brazil 8 <1%
Mexico 7 <1%
France 5 <1%
China 4 <1%
Spain 4 <1%
Other 44 2%
Unknown 2337 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 631 25%
Researcher 545 22%
Student > Master 290 12%
Student > Bachelor 177 7%
Student > Doctoral Student 128 5%
Other 337 14%
Unknown 382 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 1101 44%
Biochemistry, Genetics and Molecular Biology 488 20%
Medicine and Dentistry 92 4%
Computer Science 77 3%
Immunology and Microbiology 47 2%
Other 239 10%
Unknown 446 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 66. 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 05 March 2024.
All research outputs
#650,880
of 25,508,813 outputs
Outputs from Genome Biology
#406
of 4,484 outputs
Outputs of similar age
#2,313
of 173,555 outputs
Outputs of similar age from Genome Biology
#3
of 24 outputs
Altmetric has tracked 25,508,813 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,484 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done particularly well, scoring higher than 90% 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 173,555 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 98% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.