↓ Skip to main content

SummonChimera infers integrated viral genomes with nucleotide precision from NGS data

Overview of attention for article published in BMC Bioinformatics, October 2014
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 X users

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
46 Mendeley
citeulike
2 CiteULike
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
SummonChimera infers integrated viral genomes with nucleotide precision from NGS data
Published in
BMC Bioinformatics, October 2014
DOI 10.1186/s12859-014-0348-4
Pubmed ID
Authors

Joshua P Katz, James M Pipas

Abstract

BackgroundViral integration into a host genome is defined by two chimeric junctions that join viral and host DNA. Recently, computational tools have been developed that utilize NGS data to detect chimeric junctions. These methods identify individual viral-host junctions but do not associate chimeric pairs as an integration event. Without knowing the chimeric boundaries of an integration, its genetic content cannot be determined.ResultsSummonchimera is a Perl program that associates chimera pairs to infer the complete viral genomic integration event to the nucleotide level within single or paired-end NGS data. SummonChimera integration prediction was verified on a set of single-end IonTorrent reads from a purified Salmonella bacterium with an integrated bacteriophage. Furthermore, SummonChimera predicted integrations from experimentally verified Hepatitis B Virus chimeras within a paired-end Whole Genome Sequencing hepatocellular carcinoma tumor database.ConclusionsSummonChimera identified all experimentally verified chimeras detected by current computational methods. Further, SummonChimera integration inference precisely predicted bacteriophage integration. The application of SummonChimera to cancer NGS accurately identifies deletion of host and viral sequence during integration. The precise nucleotide determination of an integration allows prediction of viral and cellular gene transcription patterns.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 43%
Student > Ph. D. Student 11 24%
Student > Postgraduate 3 7%
Student > Master 3 7%
Student > Bachelor 2 4%
Other 1 2%
Unknown 6 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 37%
Biochemistry, Genetics and Molecular Biology 11 24%
Computer Science 4 9%
Medicine and Dentistry 4 9%
Immunology and Microbiology 3 7%
Other 1 2%
Unknown 6 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 August 2015.
All research outputs
#13,415,092
of 22,768,097 outputs
Outputs from BMC Bioinformatics
#4,192
of 7,273 outputs
Outputs of similar age
#124,517
of 260,345 outputs
Outputs of similar age from BMC Bioinformatics
#69
of 132 outputs
Altmetric has tracked 22,768,097 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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 260,345 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 50% of its contemporaries.
We're also able to compare this research output to 132 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.