↓ Skip to main content

Variation-preserving normalization unveils blind spots in gene expression profiling

Overview of attention for article published in Scientific Reports, March 2017
Altmetric Badge

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 (87th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

blogs
2 blogs
twitter
10 X users

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
58 Mendeley
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
Variation-preserving normalization unveils blind spots in gene expression profiling
Published in
Scientific Reports, March 2017
DOI 10.1038/srep42460
Pubmed ID
Authors

Carlos P. Roca, Susana I. L. Gomes, Mónica J. B. Amorim, Janeck J. Scott-Fordsmand

Abstract

RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity, but lack of reproducibility has hindered their application. A key challenge in the data analysis is the normalization of gene expression levels, which is currently performed following the implicit assumption that most genes are not differentially expressed. Here, we present a mathematical approach to normalization that makes no assumption of this sort. We have found that variation in gene expression is much larger than currently believed, and that it can be measured with available assays. Our results also explain, at least partially, the reproducibility problems encountered in transcriptomics studies. We expect that this improvement in detection will help efforts to realize the full potential of gene expression profiling, especially in analyses of cellular processes involving complex modulations of gene expression.

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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
Portugal 1 2%
Brazil 1 2%
Spain 1 2%
United States 1 2%
Unknown 52 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 28%
Student > Ph. D. Student 13 22%
Student > Master 8 14%
Student > Doctoral Student 4 7%
Other 3 5%
Other 7 12%
Unknown 7 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 34%
Biochemistry, Genetics and Molecular Biology 13 22%
Computer Science 3 5%
Neuroscience 3 5%
Engineering 2 3%
Other 6 10%
Unknown 11 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 April 2020.
All research outputs
#1,813,643
of 22,813,792 outputs
Outputs from Scientific Reports
#16,584
of 123,141 outputs
Outputs of similar age
#37,696
of 307,423 outputs
Outputs of similar age from Scientific Reports
#709
of 4,593 outputs
Altmetric has tracked 22,813,792 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 123,141 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one has done well, scoring higher than 86% 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 307,423 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 87% of its contemporaries.
We're also able to compare this research output to 4,593 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.