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AllelicImbalance: an R/ bioconductor package for detecting, managing, and visualizing allele expression imbalance data from RNA sequencing

Overview of attention for article published in BMC Bioinformatics, June 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)

Mentioned by

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14 tweeters

Citations

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12 Dimensions

Readers on

mendeley
55 Mendeley
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1 CiteULike
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Title
AllelicImbalance: an R/ bioconductor package for detecting, managing, and visualizing allele expression imbalance data from RNA sequencing
Published in
BMC Bioinformatics, June 2015
DOI 10.1186/s12859-015-0620-2
Pubmed ID
Authors

Jesper R. Gådin, Ferdinand M. van’t Hooft, Per Eriksson, Lasse Folkersen

Abstract

One aspect in which RNA sequencing is more valuable than microarray-based methods is the ability to examine the allelic imbalance of the expression of a gene. This process is often a complex task that entails quality control, alignment, and the counting of reads over heterozygous single-nucleotide polymorphisms. Allelic imbalance analysis is subject to technical biases, due to differences in the sequences of the measured alleles. Flexible bioinformatics tools are needed to ease the workflow while retaining as much RNA sequencing information as possible throughout the analysis to detect and address the possible biases. We present AllelicImblance, a software program that is designed to detect, manage, and visualize allelic imbalances comprehensively. The purpose of this software is to allow users to pose genetic questions in any RNA sequencing experiment quickly, enhancing the general utility of RNA sequencing. The visualization features can reveal notable, non-trivial allelic imbalance behavior over specific regions, such as exons. The software provides a complete framework to perform allelic imbalance analyses of aligned RNA sequencing data, from detection to visualization, within the robust and versatile management class, ASEset.

Twitter Demographics

The data shown below were collected from the profiles of 14 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
United States 1 2%
Sweden 1 2%
Germany 1 2%
Unknown 51 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 29%
Student > Ph. D. Student 9 16%
Student > Postgraduate 5 9%
Student > Master 5 9%
Student > Bachelor 3 5%
Other 11 20%
Unknown 6 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 35%
Biochemistry, Genetics and Molecular Biology 18 33%
Medicine and Dentistry 3 5%
Computer Science 3 5%
Engineering 2 4%
Other 2 4%
Unknown 8 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 2018.
All research outputs
#4,113,692
of 21,298,857 outputs
Outputs from BMC Bioinformatics
#1,623
of 6,905 outputs
Outputs of similar age
#53,725
of 250,707 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 21,298,857 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,905 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 76% 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 250,707 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% 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