↓ Skip to main content

Discovery, genotyping and characterization of structural variation and novel sequence at single nucleotide resolution from de novo genome assemblies on a population scale

Overview of attention for article published in Giga Science, December 2015
Altmetric Badge

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 (90th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
23 X users
peer_reviews
1 peer review site
facebook
2 Facebook pages

Citations

dimensions_citation
24 Dimensions

Readers on

mendeley
75 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Discovery, genotyping and characterization of structural variation and novel sequence at single nucleotide resolution from de novo genome assemblies on a population scale
Published in
Giga Science, December 2015
DOI 10.1186/s13742-015-0103-4
Pubmed ID
Authors

Siyang Liu, Shujia Huang, Junhua Rao, Weijian Ye, The Genome Denmark Consortium, Anders Krogh, Jun Wang

Abstract

Comprehensive recognition of genomic variation in one individual is important for understanding disease and developing personalized medication and treatment. Many tools based on DNA re-sequencing exist for identification of single nucleotide polymorphisms, small insertions and deletions (indels) as well as large deletions. However, these approaches consistently display a substantial bias against the recovery of complex structural variants and novel sequence in individual genomes and do not provide interpretation information such as the annotation of ancestral state and formation mechanism. We present a novel approach implemented in a single software package, AsmVar, to discover, genotype and characterize different forms of structural variation and novel sequence from population-scale de novo genome assemblies up to nucleotide resolution. Application of AsmVar to several human de novo genome assemblies captures a wide spectrum of structural variants and novel sequences present in the human population in high sensitivity and specificity. Our method provides a direct solution for investigating structural variants and novel sequences from de novo genome assemblies, facilitating the construction of population-scale pan-genomes. Our study also highlights the usefulness of the de novo assembly strategy for definition of genome structure.

X Demographics

X Demographics

The data shown below were collected from the profiles of 23 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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Netherlands 1 1%
Denmark 1 1%
France 1 1%
Unknown 70 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 31%
Student > Ph. D. Student 18 24%
Student > Master 7 9%
Student > Bachelor 4 5%
Professor > Associate Professor 4 5%
Other 12 16%
Unknown 7 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 39%
Biochemistry, Genetics and Molecular Biology 23 31%
Computer Science 7 9%
Neuroscience 2 3%
Engineering 2 3%
Other 5 7%
Unknown 7 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 13 November 2017.
All research outputs
#2,329,989
of 25,374,647 outputs
Outputs from Giga Science
#474
of 1,168 outputs
Outputs of similar age
#38,172
of 396,481 outputs
Outputs of similar age from Giga Science
#10
of 20 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% 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 gotten more attention than average, scoring higher than 59% 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 396,481 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 90% of its contemporaries.
We're also able to compare this research output to 20 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 50% of its contemporaries.