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SVachra: a tool to identify genomic structural variation in mate pair sequencing data containing inward and outward facing reads

Overview of attention for article published in BMC Genomics, October 2017
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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Title
SVachra: a tool to identify genomic structural variation in mate pair sequencing data containing inward and outward facing reads
Published in
BMC Genomics, October 2017
DOI 10.1186/s12864-017-4021-y
Pubmed ID
Authors

Oliver A. Hampton, Adam C. English, Mark Wang, William J. Salerno, Yue Liu, Donna M. Muzny, Yi Han, David A. Wheeler, Kim C. Worley, James R. Lupski, Richard A. Gibbs

Abstract

Characterization of genomic structural variation (SV) is essential to expanding the research and clinical applications of genome sequencing. Reliance upon short DNA fragment paired end sequencing has yielded a wealth of single nucleotide variants and internal sequencing read insertions-deletions, at the cost of limited SV detection. Multi-kilobase DNA fragment mate pair sequencing has supplemented the void in SV detection, but introduced new analytic challenges requiring SV detection tools specifically designed for mate pair sequencing data. Here, we introduce SVachra - Structural Variation Assessment of CHRomosomal Aberrations, a breakpoint calling program that identifies large insertions-deletions, inversions, inter- and intra-chromosomal translocations utilizing both inward and outward facing read types generated by mate pair sequencing. We demonstrate SVachra's utility by executing the program on large-insert (Illumina Nextera) mate pair sequencing data from the personal genome of a single subject (HS1011). An additional data set of long-read (Pacific BioSciences RSII) was also generated to validate SV calls from SVachra and other comparison SV calling programs. SVachra exhibited the highest validation rate and reported the widest distribution of SV types and size ranges when compared to other SV callers. SVachra is a highly specific breakpoint calling program that exhibits a more unbiased SV detection methodology than other callers.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 20%
Student > Bachelor 4 13%
Other 3 10%
Researcher 3 10%
Student > Doctoral Student 2 7%
Other 7 23%
Unknown 5 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 33%
Agricultural and Biological Sciences 7 23%
Computer Science 3 10%
Engineering 3 10%
Environmental Science 1 3%
Other 2 7%
Unknown 4 13%
Attention Score in Context

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 07 October 2017.
All research outputs
#12,861,510
of 23,005,189 outputs
Outputs from BMC Genomics
#4,433
of 10,692 outputs
Outputs of similar age
#148,119
of 323,064 outputs
Outputs of similar age from BMC Genomics
#76
of 203 outputs
Altmetric has tracked 23,005,189 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,692 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 57% 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 323,064 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 53% of its contemporaries.
We're also able to compare this research output to 203 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 61% of its contemporaries.