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Novel genomic approaches unravel genetic architecture of complex traits in apple

Overview of attention for article published in BMC Genomics, January 2013
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
75 Dimensions

Readers on

mendeley
119 Mendeley

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Summary Twitter Dimensions citations
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Title
Novel genomic approaches unravel genetic architecture of complex traits in apple
Published in
BMC Genomics, January 2013
DOI 10.1186/1471-2164-14-393
Pubmed ID
23758946
Authors

Satish Kumar, Dorian J Garrick, Marco CAM Bink, Claire Whitworth, David Chagné, Richard K Volz

Abstract

Understanding the genetic architecture of quantitative traits is important for developing genome-based crop improvement methods. Genome-wide association study (GWAS) is a powerful technique for mining novel functional variants. Using a family-based design involving 1,200 apple (Malus × domestica Borkh.) seedlings genotyped for an 8K SNP array, we report the first systematic evaluation of the relative contributions of different genomic regions to various traits related to eating quality and susceptibility to some physiological disorders. Single-SNP analyses models that accounted for population structure, or not, were compared with models fitting all markers simultaneously. The patterns of linkage disequilibrium (LD) were also investigated.

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Twitter Demographics

The data shown below were collected from the profiles of 5 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 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Netherlands 1 <1%
Italy 1 <1%
Unknown 115 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 26%
Researcher 26 22%
Student > Doctoral Student 11 9%
Student > Master 11 9%
Student > Postgraduate 7 6%
Other 24 20%
Unknown 9 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 87 73%
Biochemistry, Genetics and Molecular Biology 12 10%
Computer Science 3 3%
Psychology 2 2%
Business, Management and Accounting 1 <1%
Other 1 <1%
Unknown 13 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 25 June 2013.
All research outputs
#2,729,220
of 10,115,390 outputs
Outputs from BMC Genomics
#2,157
of 6,699 outputs
Outputs of similar age
#35,936
of 131,140 outputs
Outputs of similar age from BMC Genomics
#63
of 166 outputs
Altmetric has tracked 10,115,390 research outputs across all sources so far. This one has received more attention than most of these and is in the 55th percentile.
So far Altmetric has tracked 6,699 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 60% 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 131,140 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 166 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.

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