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MagiCMicroRna: a web implementation of AgiMicroRna using shiny

Overview of attention for article published in Source Code for Biology and Medicine, March 2015
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4 X users
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1 Facebook page

Citations

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9 Dimensions

Readers on

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16 Mendeley
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2 CiteULike
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Title
MagiCMicroRna: a web implementation of AgiMicroRna using shiny
Published in
Source Code for Biology and Medicine, March 2015
DOI 10.1186/s13029-015-0035-5
Pubmed ID
Authors

Maarten LJ Coonen, Daniel HJ Theunissen, Jos CS Kleinjans, Danyel GJ Jennen

Abstract

MicroRNA expression can be quantified using sequencing techniques or commercial microRNA-expression arrays. Recently, the AgiMicroRna R-package was published that enabled systematic preprocessing and statistical analysis for Agilent microRNA arrays. Here we describe MagiCMicroRna, which is a user-friendly web interface for this package, together with a new filtering approach. We used MagiCMicroRna to normalize and filter an Agilent miRNA microarray dataset of cancerous and normal tissues from 14 different patients. With the standard filtering procedure, 250 out of 817 microRNAs remained, whereas the new group-specific filtering approach resulted in broader datasets for further analysis in most groups (>279 microRNAs remaining). The user-friendly web interface of MagiCMicroRna enables researchers to normalize and filter Agilent microarrays by the click of one button. Furthermore, MagiCMicroRna provides flexibility in choosing the filtering method. The new group-specific filtering approach lead to an increased number and additional tissue-specific microRNAs remaining for subsequent analysis compared to the standard procedure. The MagiCMicroRna web interface and source code can be downloaded from https://bitbucket.org/mutgx/magicmicrorna.git.

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X Demographics

The data shown below were collected from the profiles of 4 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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 6%
Unknown 15 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 38%
Student > Bachelor 3 19%
Other 1 6%
Professor 1 6%
Lecturer 1 6%
Other 2 13%
Unknown 2 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 25%
Engineering 3 19%
Computer Science 2 13%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Mathematics 1 6%
Other 3 19%
Unknown 2 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 04 April 2015.
All research outputs
#14,429,961
of 23,577,761 outputs
Outputs from Source Code for Biology and Medicine
#69
of 127 outputs
Outputs of similar age
#136,520
of 264,864 outputs
Outputs of similar age from Source Code for Biology and Medicine
#1
of 4 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% 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 41st percentile – i.e., 41% 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 264,864 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 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