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Assessing structural variation in a personal genome—towards a human reference diploid genome

Overview of attention for article published in BMC Genomics, April 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

blogs
2 blogs
twitter
48 X users
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
148 Dimensions

Readers on

mendeley
291 Mendeley
citeulike
2 CiteULike
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Title
Assessing structural variation in a personal genome—towards a human reference diploid genome
Published in
BMC Genomics, April 2015
DOI 10.1186/s12864-015-1479-3
Pubmed ID
Authors

Adam C English, William J Salerno, Oliver A Hampton, Claudia Gonzaga-Jauregui, Shruthi Ambreth, Deborah I Ritter, Christine R Beck, Caleb F Davis, Mahmoud Dahdouli, Singer Ma, Andrew Carroll, Narayanan Veeraraghavan, Jeremy Bruestle, Becky Drees, Alex Hastie, Ernest T Lam, Simon White, Pamela Mishra, Min Wang, Yi Han, Feng Zhang, Pawel Stankiewicz, David A Wheeler, Jeffrey G Reid, Donna M Muzny, Jeffrey Rogers, Aniko Sabo, Kim C Worley, James R Lupski, Eric Boerwinkle, Richard A Gibbs

Abstract

Characterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods. We demonstrate Parliament's efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus. HS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.

X Demographics

X Demographics

The data shown below were collected from the profiles of 48 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 291 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 2%
Norway 2 <1%
Germany 1 <1%
Italy 1 <1%
Brazil 1 <1%
Sweden 1 <1%
Netherlands 1 <1%
Mexico 1 <1%
India 1 <1%
Other 2 <1%
Unknown 273 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 78 27%
Student > Ph. D. Student 75 26%
Student > Bachelor 20 7%
Student > Master 17 6%
Professor > Associate Professor 16 5%
Other 48 16%
Unknown 37 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 110 38%
Biochemistry, Genetics and Molecular Biology 71 24%
Computer Science 24 8%
Medicine and Dentistry 12 4%
Engineering 7 2%
Other 21 7%
Unknown 46 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 39. 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 21 October 2016.
All research outputs
#1,019,059
of 24,862,067 outputs
Outputs from BMC Genomics
#139
of 11,092 outputs
Outputs of similar age
#12,851
of 269,990 outputs
Outputs of similar age from BMC Genomics
#3
of 269 outputs
Altmetric has tracked 24,862,067 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,092 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 98% 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 269,990 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 95% of its contemporaries.
We're also able to compare this research output to 269 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.