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A comparison across non-model animals suggests an optimal sequencing depth for de novotranscriptome assembly

Overview of attention for article published in BMC Genomics, March 2013
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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 (95th percentile)

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1 Facebook page

Citations

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82 Dimensions

Readers on

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267 Mendeley
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1 CiteULike
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Title
A comparison across non-model animals suggests an optimal sequencing depth for de novotranscriptome assembly
Published in
BMC Genomics, March 2013
DOI 10.1186/1471-2164-14-167
Pubmed ID
Authors

Warren R Francis, Lynne M Christianson, Rainer Kiko, Meghan L Powers, Nathan C Shaner, Steven H D Haddock

Abstract

The lack of genomic resources can present challenges for studies of non-model organisms. Transcriptome sequencing offers an attractive method to gather information about genes and gene expression without the need for a reference genome. However, it is unclear what sequencing depth is adequate to assemble the transcriptome de novo for these purposes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 30 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 267 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 3%
Germany 5 2%
France 4 1%
Japan 3 1%
Brazil 2 <1%
Australia 2 <1%
Spain 2 <1%
Canada 2 <1%
United Kingdom 2 <1%
Other 6 2%
Unknown 231 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 73 27%
Researcher 61 23%
Student > Master 35 13%
Student > Bachelor 16 6%
Student > Doctoral Student 15 6%
Other 50 19%
Unknown 17 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 166 62%
Biochemistry, Genetics and Molecular Biology 46 17%
Computer Science 8 3%
Immunology and Microbiology 5 2%
Environmental Science 5 2%
Other 17 6%
Unknown 20 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 01 December 2015.
All research outputs
#2,201,674
of 25,371,288 outputs
Outputs from BMC Genomics
#556
of 11,244 outputs
Outputs of similar age
#17,718
of 208,473 outputs
Outputs of similar age from BMC Genomics
#8
of 183 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 95% 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 208,473 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 183 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 95% of its contemporaries.