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De novo construction of a “Gene-space” for diploid plant genome rich in repetitive sequences by an iterative Process of Extraction and Assembly of NGS reads (iPEA protocol) with limited computing…

Overview of attention for article published in BMC Research Notes, February 2016
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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 (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

blogs
1 blog
twitter
3 tweeters

Citations

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6 Dimensions

Readers on

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15 Mendeley
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Title
De novo construction of a “Gene-space” for diploid plant genome rich in repetitive sequences by an iterative Process of Extraction and Assembly of NGS reads (iPEA protocol) with limited computing resources
Published in
BMC Research Notes, February 2016
DOI 10.1186/s13104-016-1903-z
Pubmed ID
Authors

Christelle Aluome, Grégoire Aubert, Susete Alves Carvalho, Marie-Christine Le Paslier, Judith Burstin, Dominique Brunel

Abstract

The continuing increase in size and quality of the "short reads" raw data is a significant help for the quality of the assembly obtained through various bioinformatics tools. However, building a reference genome sequence for most plant species remains a significant challenge due to the large number of repeated sequences which are problematic for a whole-genome quality de novo assembly. Furthermore, for most SNP identification approaches in plant genetics and breeding, only the "Gene-space" regions including the promoter, exon and intron sequences are considered. We developed the iPea protocol to produce a de novo Gene-space assembly by reconstructing, in an iterative way, the non-coding sequence flanking the Unigene cDNA sequence through addition of next-generation DNA-seq data. The approach was elaborated with the large diploid genome of pea (Pisum sativum L.), rich in repetitive sequences. The final Gene-space assembly included 35,400 contigs (97 Mb), covering 88 % of the 40,227 contigs (53.1 Mb) of the PsCam_low-copy Unigen set. Its accuracy was validated by the results of the built GenoPea 13.2 K SNP Array. The iPEA protocol allows the reconstruction of a Gene-space based from RNA-Seq and DNA-seq data with limited computing resources.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 7%
United States 1 7%
France 1 7%
Unknown 12 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 33%
Student > Master 2 13%
Professor 2 13%
Unspecified 1 7%
Other 1 7%
Other 2 13%
Unknown 2 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 53%
Biochemistry, Genetics and Molecular Biology 2 13%
Computer Science 2 13%
Unspecified 1 7%
Unknown 2 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 20 February 2016.
All research outputs
#1,326,746
of 10,618,812 outputs
Outputs from BMC Research Notes
#245
of 2,442 outputs
Outputs of similar age
#51,067
of 293,917 outputs
Outputs of similar age from BMC Research Notes
#22
of 118 outputs
Altmetric has tracked 10,618,812 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,442 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 89% 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 293,917 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 82% of its contemporaries.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.