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An ensemble approach to accurately detect somatic mutations using SomaticSeq

Overview of attention for article published in Genome Biology, September 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

31 tweeters
4 patents
2 Facebook pages
1 Wikipedia page
1 Google+ user


88 Dimensions

Readers on

182 Mendeley
3 CiteULike
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An ensemble approach to accurately detect somatic mutations using SomaticSeq
Published in
Genome Biology, September 2015
DOI 10.1186/s13059-015-0758-2
Pubmed ID

Li Tai Fang, Pegah Tootoonchi Afshar, Aparna Chhibber, Marghoob Mohiyuddin, Yu Fan, John C. Mu, Greg Gibeling, Sharon Barr, Narges Bani Asadi, Mark B. Gerstein, Daniel C. Koboldt, Wenyi Wang, Wing H. Wong, Hugo Y.K. Lam


SomaticSeq is an accurate somatic mutation detection pipeline implementing a stochastic boosting algorithm to produce highly accurate somatic mutation calls for both single nucleotide variants and small insertions and deletions. The workflow currently incorporates five state-of-the-art somatic mutation callers, and extracts over 70 individual genomic and sequencing features for each candidate site. A training set is provided to an adaptively boosted decision tree learner to create a classifier for predicting mutation statuses. We validate our results with both synthetic and real data. We report that SomaticSeq is able to achieve better overall accuracy than any individual tool incorporated.

Twitter Demographics

Twitter Demographics

The data shown below were collected from the profiles of 31 tweeters 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 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 2 1%
United States 2 1%
Korea, Republic of 1 <1%
Netherlands 1 <1%
United Kingdom 1 <1%
Australia 1 <1%
Taiwan 1 <1%
New Zealand 1 <1%
Unknown 172 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 50 27%
Student > Master 27 15%
Student > Ph. D. Student 25 14%
Student > Bachelor 13 7%
Other 9 5%
Other 23 13%
Unknown 35 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 45 25%
Agricultural and Biological Sciences 45 25%
Computer Science 24 13%
Medicine and Dentistry 13 7%
Engineering 8 4%
Other 9 5%
Unknown 38 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 29. 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 11 October 2021.
All research outputs
of 24,003,070 outputs
Outputs from Genome Biology
of 4,279 outputs
Outputs of similar age
of 276,099 outputs
Outputs of similar age from Genome Biology
of 82 outputs
Altmetric has tracked 24,003,070 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 4,279 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.9. This one has done well, scoring higher than 75% 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 276,099 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 82 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 70% of its contemporaries.