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HiView: an integrative genome browser to leverage Hi-C results for the interpretation of GWAS variants

Overview of attention for article published in BMC Research Notes, March 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

twitter
6 tweeters

Citations

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8 Dimensions

Readers on

mendeley
31 Mendeley
citeulike
1 CiteULike
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Title
HiView: an integrative genome browser to leverage Hi-C results for the interpretation of GWAS variants
Published in
BMC Research Notes, March 2016
DOI 10.1186/s13104-016-1947-0
Pubmed ID
Authors

Zheng Xu, Guosheng Zhang, Qing Duan, Shengjie Chai, Baqun Zhang, Cong Wu, Fulai Jin, Feng Yue, Yun Li, Ming Hu

Abstract

Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits and diseases. However, most of them are located in the non-protein coding regions, and therefore it is challenging to hypothesize the functions of these non-coding GWAS variants. Recent large efforts such as the ENCODE and Roadmap Epigenomics projects have predicted a large number of regulatory elements. However, the target genes of these regulatory elements remain largely unknown. Chromatin conformation capture based technologies such as Hi-C can directly measure the chromatin interactions and have generated an increasingly comprehensive catalog of the interactome between the distal regulatory elements and their potential target genes. Leveraging such information revealed by Hi-C holds the promise of elucidating the functions of genetic variants in human diseases. In this work, we present HiView, the first integrative genome browser to leverage Hi-C results for the interpretation of GWAS variants. HiView is able to display Hi-C data and statistical evidence for chromatin interactions in genomic regions surrounding any given GWAS variant, enabling straightforward visualization and interpretation. We believe that as the first GWAS variants-centered Hi-C genome browser, HiView is a useful tool guiding post-GWAS functional genomics studies. HiView is freely accessible at: http://www.unc.edu/~yunmli/HiView .

Twitter Demographics

The data shown below were collected from the profiles of 6 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 3%
Unknown 30 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 39%
Researcher 9 29%
Lecturer 3 10%
Professor 1 3%
Student > Bachelor 1 3%
Other 2 6%
Unknown 3 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 35%
Agricultural and Biological Sciences 9 29%
Computer Science 3 10%
Mathematics 1 3%
Physics and Astronomy 1 3%
Other 2 6%
Unknown 4 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 March 2016.
All research outputs
#1,679,626
of 7,386,232 outputs
Outputs from BMC Research Notes
#433
of 1,876 outputs
Outputs of similar age
#82,855
of 276,558 outputs
Outputs of similar age from BMC Research Notes
#28
of 112 outputs
Altmetric has tracked 7,386,232 research outputs across all sources so far. Compared to these this one has done well and is in the 77th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,876 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 76% 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 276,558 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 69% of its contemporaries.
We're also able to compare this research output to 112 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.