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JAFFA: High sensitivity transcriptome-focused fusion gene detection

Overview of attention for article published in Genome Medicine, May 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)

Mentioned by

2 blogs
49 tweeters
2 Facebook pages
1 Q&A thread


120 Dimensions

Readers on

168 Mendeley
4 CiteULike
JAFFA: High sensitivity transcriptome-focused fusion gene detection
Published in
Genome Medicine, May 2015
DOI 10.1186/s13073-015-0167-x
Pubmed ID

Nadia M Davidson, Ian J Majewski, Alicia Oshlack


Genomic instability is a hallmark of cancer and, as such, structural alterations and fusion genes are common events in the cancer landscape. RNA sequencing (RNA-Seq) is a powerful method for profiling cancers, but current methods for identifying fusion genes are optimised for short reads. JAFFA (https://github.com/Oshlack/JAFFA/wiki) is a sensitive fusion detection method that outperforms other methods with reads of 100 bp or greater. JAFFA compares a cancer transcriptome to the reference transcriptome, rather than the genome, where the cancer transcriptome is inferred using long reads directly or by de novo assembling short reads.

Twitter Demographics

The data shown below were collected from the profiles of 49 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 168 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
Germany 3 2%
Norway 1 <1%
Korea, Republic of 1 <1%
Brazil 1 <1%
Indonesia 1 <1%
New Zealand 1 <1%
United Kingdom 1 <1%
Belgium 1 <1%
Other 1 <1%
Unknown 152 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 19%
Researcher 30 18%
Student > Master 24 14%
Student > Bachelor 16 10%
Other 11 7%
Other 28 17%
Unknown 27 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 52 31%
Biochemistry, Genetics and Molecular Biology 49 29%
Computer Science 14 8%
Medicine and Dentistry 10 6%
Unspecified 5 3%
Other 7 4%
Unknown 31 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 41. 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 25 October 2021.
All research outputs
of 22,514,578 outputs
Outputs from Genome Medicine
of 1,421 outputs
Outputs of similar age
of 247,376 outputs
Outputs of similar age from Genome Medicine
of 1 outputs
Altmetric has tracked 22,514,578 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,421 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.4. This one has done well, scoring higher than 88% 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 247,376 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 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