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SERE: Single-parameter quality control and sample comparison for RNA-Seq

Overview of attention for article published in BMC Genomics, October 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

blogs
2 blogs
twitter
10 X users
patent
1 patent

Citations

dimensions_citation
126 Dimensions

Readers on

mendeley
142 Mendeley
citeulike
8 CiteULike
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Title
SERE: Single-parameter quality control and sample comparison for RNA-Seq
Published in
BMC Genomics, October 2012
DOI 10.1186/1471-2164-13-524
Pubmed ID
Authors

Stefan K Schulze, Rahul Kanwar, Meike Gölzenleuchter, Terry M Therneau, Andreas S Beutler

Abstract

Assessing the reliability of experimental replicates (or global alterations corresponding to different experimental conditions) is a critical step in analyzing RNA-Seq data. Pearson's correlation coefficient r has been widely used in the RNA-Seq field even though its statistical characteristics may be poorly suited to the task.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 142 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 5%
United Kingdom 3 2%
Brazil 2 1%
Sweden 1 <1%
Slovenia 1 <1%
Italy 1 <1%
Unknown 127 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 40 28%
Student > Ph. D. Student 30 21%
Student > Master 16 11%
Other 9 6%
Student > Doctoral Student 8 6%
Other 24 17%
Unknown 15 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 75 53%
Biochemistry, Genetics and Molecular Biology 30 21%
Medicine and Dentistry 6 4%
Engineering 5 4%
Computer Science 4 3%
Other 5 4%
Unknown 17 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 12 May 2022.
All research outputs
#1,683,172
of 23,881,329 outputs
Outputs from BMC Genomics
#378
of 10,793 outputs
Outputs of similar age
#10,848
of 174,258 outputs
Outputs of similar age from BMC Genomics
#3
of 129 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,793 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 96% 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 174,258 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 93% of its contemporaries.
We're also able to compare this research output to 129 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 98% of its contemporaries.