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DEApp: an interactive web interface for differential expression analysis of next generation sequence data

Overview of attention for article published in Source Code for Biology and Medicine, February 2017
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Title
DEApp: an interactive web interface for differential expression analysis of next generation sequence data
Published in
Source Code for Biology and Medicine, February 2017
DOI 10.1186/s13029-017-0063-4
Pubmed ID
Authors

Yan Li, Jorge Andrade

Abstract

A growing trend in the biomedical community is the use of Next Generation Sequencing (NGS) technologies in genomics research. The complexity of downstream differential expression (DE) analysis is however still challenging, as it requires sufficient computer programing and command-line knowledge. Furthermore, researchers often need to evaluate and visualize interactively the effect of using differential statistical and error models, assess the impact of selecting different parameters and cutoffs, and finally explore the overlapping consensus of cross-validated results obtained with different methods. This represents a bottleneck that slows down or impedes the adoption of NGS technologies in many labs. We developed DEApp, an interactive and dynamic web application for differential expression analysis of count based NGS data. This application enables models selection, parameter tuning, cross validation and visualization of results in a user-friendly interface. DEApp enables labs with no access to full time bioinformaticians to exploit the advantages of NGS applications in biomedical research. This application is freely available at https://yanli.shinyapps.io/DEAppand https://gallery.shinyapps.io/DEApp.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 90 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 21%
Student > Ph. D. Student 16 18%
Student > Doctoral Student 13 14%
Student > Master 10 11%
Student > Bachelor 9 10%
Other 13 14%
Unknown 10 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 29 32%
Agricultural and Biological Sciences 18 20%
Computer Science 9 10%
Medicine and Dentistry 5 6%
Immunology and Microbiology 4 4%
Other 11 12%
Unknown 14 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 13 February 2017.
All research outputs
#15,440,760
of 22,950,943 outputs
Outputs from Source Code for Biology and Medicine
#85
of 127 outputs
Outputs of similar age
#257,084
of 420,783 outputs
Outputs of similar age from Source Code for Biology and Medicine
#1
of 2 outputs
Altmetric has tracked 22,950,943 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 25th percentile – i.e., 25% 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 420,783 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 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