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PacBio-LITS: a large-insert targeted sequencing method for characterization of human disease-associated chromosomal structural variations

Overview of attention for article published in BMC Genomics, March 2015
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  • 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 (98th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
18 X users
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1 patent
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

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64 Dimensions

Readers on

mendeley
164 Mendeley
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1 CiteULike
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Title
PacBio-LITS: a large-insert targeted sequencing method for characterization of human disease-associated chromosomal structural variations
Published in
BMC Genomics, March 2015
DOI 10.1186/s12864-015-1370-2
Pubmed ID
Authors

Min Wang, Christine R Beck, Adam C English, Qingchang Meng, Christian Buhay, Yi Han, Harsha V Doddapaneni, Fuli Yu, Eric Boerwinkle, James R Lupski, Donna M Muzny, Richard A Gibbs

Abstract

Generation of long (>5 Kb) DNA sequencing reads provides an approach for interrogation of complex regions in the human genome. Currently, large-insert whole genome sequencing (WGS) technologies from Pacific Biosciences (PacBio) enable analysis of chromosomal structural variations (SVs), but the cost to achieve the required sequence coverage across the entire human genome is high. We developed a method (termed PacBio-LITS) that combines oligonucleotide-based DNA target-capture enrichment technologies with PacBio large-insert library preparation to facilitate SV studies at specific chromosomal regions. PacBio-LITS provides deep sequence coverage at the specified sites at substantially reduced cost compared with PacBio WGS. The efficacy of PacBio-LITS is illustrated by delineating the breakpoint junctions of low copy repeat (LCR)-associated complex structural rearrangements on chr17p11.2 in patients diagnosed with Potocki-Lupski syndrome (PTLS; MIM#610883). We successfully identified previously determined breakpoint junctions in three PTLS cases, and also were able to discover novel junctions in repetitive sequences, including LCR-mediated breakpoints. The new information has enabled us to propose mechanisms for formation of these structural variants. The new method leverages the cost efficiency of targeted capture-sequencing as well as the mappability and scaffolding capabilities of long sequencing reads generated by the PacBio platform. It is therefore suitable for studying complex SVs, especially those involving LCRs, inversions, and the generation of chimeric Alu elements at the breakpoints. Other genomic research applications, such as haplotype phasing and small insertion and deletion validation could also benefit from this technology.

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 164 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
France 2 1%
United Kingdom 2 1%
Netherlands 1 <1%
Austria 1 <1%
Switzerland 1 <1%
Singapore 1 <1%
Italy 1 <1%
Unknown 150 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 52 32%
Student > Ph. D. Student 33 20%
Other 17 10%
Student > Bachelor 10 6%
Student > Master 10 6%
Other 27 16%
Unknown 15 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 70 43%
Biochemistry, Genetics and Molecular Biology 47 29%
Medicine and Dentistry 10 6%
Engineering 4 2%
Computer Science 4 2%
Other 9 5%
Unknown 20 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 37. 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 29 June 2021.
All research outputs
#932,906
of 22,796,179 outputs
Outputs from BMC Genomics
#137
of 10,648 outputs
Outputs of similar age
#13,073
of 263,733 outputs
Outputs of similar age from BMC Genomics
#4
of 283 outputs
Altmetric has tracked 22,796,179 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 10,648 research outputs from this source. They receive a mean Attention Score of 4.7. 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 263,733 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 283 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 98% of its contemporaries.