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Recommendations on e-infrastructures for next-generation sequencing

Overview of attention for article published in Giga Science, June 2016
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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 (94th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
51 X users
peer_reviews
1 peer review site
facebook
3 Facebook pages
googleplus
3 Google+ users

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
110 Mendeley
citeulike
1 CiteULike
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Title
Recommendations on e-infrastructures for next-generation sequencing
Published in
Giga Science, June 2016
DOI 10.1186/s13742-016-0132-7
Pubmed ID
Authors

Ola Spjuth, Erik Bongcam-Rudloff, Johan Dahlberg, Martin Dahlö, Aleksi Kallio, Luca Pireddu, Francesco Vezzi, Eija Korpelainen

Abstract

With ever-increasing amounts of data being produced by next-generation sequencing (NGS) experiments, the requirements placed on supporting e-infrastructures have grown. In this work, we provide recommendations based on the collective experiences from participants in the EU COST Action SeqAhead for the tasks of data preprocessing, upstream processing, data delivery, and downstream analysis, as well as long-term storage and archiving. We cover demands on computational and storage resources, networks, software stacks, automation of analysis, education, and also discuss emerging trends in the field. E-infrastructures for NGS require substantial effort to set up and maintain over time, and with sequencing technologies and best practices for data analysis evolving rapidly it is important to prioritize both processing capacity and e-infrastructure flexibility when making strategic decisions to support the data analysis demands of tomorrow. Due to increasingly demanding technical requirements we recommend that e-infrastructure development and maintenance be handled by a professional service unit, be it internal or external to the organization, and emphasis should be placed on collaboration between researchers and IT professionals.

X Demographics

X Demographics

The data shown below were collected from the profiles of 51 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 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 2 2%
Hungary 1 <1%
Italy 1 <1%
United Kingdom 1 <1%
Korea, Republic of 1 <1%
United States 1 <1%
Unknown 103 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 31%
Student > Ph. D. Student 15 14%
Student > Master 15 14%
Student > Bachelor 7 6%
Professor 5 5%
Other 19 17%
Unknown 15 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 23%
Biochemistry, Genetics and Molecular Biology 21 19%
Computer Science 17 15%
Medicine and Dentistry 6 5%
Engineering 5 5%
Other 16 15%
Unknown 20 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 36. 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 22 May 2017.
All research outputs
#1,133,071
of 25,394,764 outputs
Outputs from Giga Science
#183
of 1,168 outputs
Outputs of similar age
#20,938
of 355,837 outputs
Outputs of similar age from Giga Science
#7
of 13 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,168 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.8. This one has done well, scoring higher than 84% 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 355,837 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 94% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.