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Use of RNA sequencing to evaluate rheumatic disease patients

Overview of attention for article published in Arthritis Research & Therapy, July 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
10 tweeters

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
66 Mendeley
citeulike
1 CiteULike
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Title
Use of RNA sequencing to evaluate rheumatic disease patients
Published in
Arthritis Research & Therapy, July 2015
DOI 10.1186/s13075-015-0677-3
Pubmed ID
Authors

Eugenia G Giannopoulou, Olivier Elemento, Lionel B Ivashkiv

Abstract

Studying the factors that control gene expression is of substantial importance for rheumatic diseases with poorly understood etiopathogenesis. In the past, gene expression microarrays have been used to measure transcript abundance on a genome-wide scale in a particular cell, tissue or organ. Microarray analysis has led to gene signatures that differentiate rheumatic diseases, and stages of a disease, as well as response to treatments. Nowadays, however, with the advent of next-generation sequencing methods, massive parallel sequencing of RNA tends to be the technology of choice for gene expression profiling, due to several advantages over microarrays, as well as for the detection of non-coding transcripts and alternative splicing events. In this review, we describe how RNA sequencing enables unbiased interrogation of the abundance and complexity of the transcriptome, and present a typical experimental workflow and bioinformatics tools that are often used for RNA sequencing analysis. We also discuss different uses of this next-generation sequencing technology to evaluate rheumatic disease patients and investigate the pathogenesis of rheumatic diseases such as rheumatoid arthritis, systemic lupus erythematosus, juvenile idiopathic arthritis and Sjögren's syndrome.

Twitter Demographics

The data shown below were collected from the profiles of 10 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 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Unknown 65 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 21%
Researcher 14 21%
Student > Bachelor 10 15%
Student > Master 7 11%
Student > Doctoral Student 6 9%
Other 12 18%
Unknown 3 5%
Readers by discipline Count As %
Medicine and Dentistry 24 36%
Biochemistry, Genetics and Molecular Biology 12 18%
Agricultural and Biological Sciences 11 17%
Immunology and Microbiology 6 9%
Computer Science 2 3%
Other 4 6%
Unknown 7 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 07 July 2015.
All research outputs
#2,679,978
of 12,451,992 outputs
Outputs from Arthritis Research & Therapy
#683
of 1,983 outputs
Outputs of similar age
#49,876
of 233,834 outputs
Outputs of similar age from Arthritis Research & Therapy
#8
of 36 outputs
Altmetric has tracked 12,451,992 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,983 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has gotten more attention than average, scoring higher than 68% 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 233,834 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 78% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.