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A quantitative reference transcriptome for Nematostella vectensis earlyembryonic development: a pipeline for de novo assembly in emergingmodel systems

Overview of attention for article published in EvoDevo, June 2013
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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 (76th percentile)

Mentioned by

twitter
10 tweeters

Citations

dimensions_citation
54 Dimensions

Readers on

mendeley
113 Mendeley
citeulike
1 CiteULike
Title
A quantitative reference transcriptome for Nematostella vectensis earlyembryonic development: a pipeline for de novo assembly in emergingmodel systems
Published in
EvoDevo, June 2013
DOI 10.1186/2041-9139-4-16
Pubmed ID
Authors

Sarah Tulin, Derek Aguiar, Sorin Istrail, Joel Smith

Abstract

The de novo assembly of transcriptomes from short shotgun sequences raises challenges due to random and non-random sequencing biases and inherent transcript complexity. We sought to define a pipeline for de novo transcriptome assembly to aid researchers working with emerging model systems where well annotated genome assemblies are not available as a reference. To detail this experimental and computational method, we used early embryos of the sea anemone, Nematostella vectensis, an emerging model system for studies of animal body plan evolution. We performed RNA-seq on embryos up to 24 h of development using Illumina HiSeq technology and evaluated independent de novo assembly methods. The resulting reads were assembled using either the Trinity assembler on all quality controlled reads or both the Velvet and Oases assemblers on reads passing a stringent digital normalization filter. A control set of mRNA standards from the National Institute of Standards and Technology (NIST) was included in our experimental pipeline to invest our transcriptome with quantitative information on absolute transcript levels and to provide additional quality control.

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

Geographical breakdown

Country Count As %
United States 3 3%
Spain 2 2%
Germany 1 <1%
United Kingdom 1 <1%
Chile 1 <1%
Israel 1 <1%
Mexico 1 <1%
Unknown 103 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 28%
Researcher 25 22%
Student > Master 10 9%
Professor > Associate Professor 8 7%
Student > Bachelor 7 6%
Other 18 16%
Unknown 13 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 64 57%
Biochemistry, Genetics and Molecular Biology 18 16%
Computer Science 4 4%
Engineering 3 3%
Psychology 2 2%
Other 8 7%
Unknown 14 12%

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 18 June 2013.
All research outputs
#5,556,825
of 22,711,645 outputs
Outputs from EvoDevo
#140
of 317 outputs
Outputs of similar age
#46,311
of 195,516 outputs
Outputs of similar age from EvoDevo
#1
of 2 outputs
Altmetric has tracked 22,711,645 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 317 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one has gotten more attention than average, scoring higher than 55% 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 195,516 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 76% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them