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Batch effect detection and correction in RNA-seq data using machine-learning-based automated assessment of quality

Overview of attention for article published in BMC Bioinformatics, July 2022
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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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

blogs
1 blog
twitter
33 X users

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
63 Mendeley
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Title
Batch effect detection and correction in RNA-seq data using machine-learning-based automated assessment of quality
Published in
BMC Bioinformatics, July 2022
DOI 10.1186/s12859-022-04775-y
Pubmed ID
Authors

Maximilian Sprang, Miguel A. Andrade-Navarro, Jean-Fred Fontaine

X Demographics

X Demographics

The data shown below were collected from the profiles of 33 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 16%
Student > Ph. D. Student 8 13%
Unspecified 6 10%
Student > Bachelor 3 5%
Other 3 5%
Other 6 10%
Unknown 27 43%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 21%
Unspecified 6 10%
Agricultural and Biological Sciences 4 6%
Computer Science 4 6%
Immunology and Microbiology 2 3%
Other 7 11%
Unknown 27 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 08 August 2023.
All research outputs
#1,590,980
of 25,307,332 outputs
Outputs from BMC Bioinformatics
#249
of 7,672 outputs
Outputs of similar age
#34,674
of 428,598 outputs
Outputs of similar age from BMC Bioinformatics
#5
of 154 outputs
Altmetric has tracked 25,307,332 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,672 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. 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 428,598 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 91% of its contemporaries.
We're also able to compare this research output to 154 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 97% of its contemporaries.