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Pegasus: a comprehensive annotation and prediction tool for detection of driver gene fusions in cancer

Overview of attention for article published in BMC Systems Biology, September 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#18 of 1,139)
  • High Attention Score compared to outputs of the same age (93rd percentile)

Mentioned by

blogs
1 blog
twitter
24 tweeters
patent
1 patent
q&a
1 Q&A thread

Citations

dimensions_citation
56 Dimensions

Readers on

mendeley
119 Mendeley
citeulike
2 CiteULike
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Title
Pegasus: a comprehensive annotation and prediction tool for detection of driver gene fusions in cancer
Published in
BMC Systems Biology, September 2014
DOI 10.1186/s12918-014-0097-z
Pubmed ID
Authors

Francesco Abate, Sakellarios Zairis, Elisa Ficarra, Andrea Acquaviva, Chris H Wiggins, Veronique Frattini, Anna Lasorella, Antonio Iavarone, Giorgio Inghirami, Raul Rabadan

Abstract

BackgroundThe extraordinary success of imatinib in the treatment of BCR-ABL1 associated cancers underscores the need to identify novel functional gene fusions in cancer. RNA sequencing offers a genome-wide view of expressed transcripts, uncovering biologically functional gene fusions. Although several bioinformatics tools are already available for the detection of putative fusion transcripts, candidate event lists are plagued with non-functional read-through events, reverse transcriptase template switching events, incorrect mapping, and other systematic errors. Such lists lack any indication of oncogenic relevance, and they are too large for exhaustive experimental validation.ResultsWe have designed and implemented a pipeline, Pegasus, for the annotation and prediction of biologically functional gene fusion candidates. Pegasus provides a common interface for various gene fusion detection tools, reconstruction of novel fusion proteins, reading-frame-aware annotation of preserved/lost functional domains, and data-driven classification of oncogenic potential. Pegasus dramatically streamlines the search for oncogenic gene fusions, bridging the gap between raw RNA-Seq data and a final, tractable list of candidates for experimental validation.ConclusionWe show the effectiveness of Pegasus in predicting new driver fusions in 176 RNA-Seq samples of glioblastoma multiforme (GBM) and 23 cases of anaplastic large cell lymphoma (ALCL). Contact: [email protected]

Twitter Demographics

The data shown below were collected from the profiles of 24 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 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Norway 1 <1%
Australia 1 <1%
United Kingdom 1 <1%
South Africa 1 <1%
Japan 1 <1%
Belgium 1 <1%
Unknown 111 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 28%
Researcher 33 28%
Student > Bachelor 15 13%
Student > Master 12 10%
Student > Doctoral Student 9 8%
Other 11 9%
Unknown 6 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 33%
Biochemistry, Genetics and Molecular Biology 31 26%
Computer Science 11 9%
Medicine and Dentistry 11 9%
Engineering 7 6%
Other 8 7%
Unknown 12 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 10 June 2021.
All research outputs
#1,247,976
of 21,353,399 outputs
Outputs from BMC Systems Biology
#18
of 1,139 outputs
Outputs of similar age
#14,124
of 216,321 outputs
Outputs of similar age from BMC Systems Biology
#1
of 1 outputs
Altmetric has tracked 21,353,399 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,139 research outputs from this source. They receive a mean Attention Score of 3.5. 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 216,321 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 93% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them