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SCExV: a webtool for the analysis and visualisation of single cell qRT-PCR data

Overview of attention for article published in BMC Bioinformatics, October 2015
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Mentioned by

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3 tweeters

Citations

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14 Dimensions

Readers on

mendeley
19 Mendeley
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1 CiteULike
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Title
SCExV: a webtool for the analysis and visualisation of single cell qRT-PCR data
Published in
BMC Bioinformatics, October 2015
DOI 10.1186/s12859-015-0757-z
Pubmed ID
Authors

Stefan Lang, Amol Ugale, Eva Erlandsson, Göran Karlsson, David Bryder, Shamit Soneji

Abstract

Single cell gene expression assays have become a powerful tool with which to dissect heterogeneous populations. While methods and software exist to interrogate such data, what has been lacking is a unified solution combining analysis and visualisation which is also accessible and intuitive for use by non-bioinformaticians, as well as bioinformaticians. We present the Single cell expression visualiser (SCExV), a webtool developed to expedite the analysis of single cell qRT-PCR data. SCExV is able to take any data matrix of Ct values as an input, but can handle files exported by the Fluidigm Biomark platform directly. In addition, SCExV also accepts and automatically integrates cell surface marker intensity values which are measured during index sorting. This allows the user to directly visualise relationships between a single cell gene expression profile and the immunophenotype of the interrogated cell. SCExV is a freely available webtool created to import, filter, analyse, and visualise single cell gene expression data whilst being able to simultaneously consider cellular immunophenotype. SCExV is designed to be intuitive to use whilst maintaining advanced functionality and flexibility in how analyses are performed.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 26%
Other 3 16%
Student > Bachelor 3 16%
Student > Ph. D. Student 3 16%
Professor 1 5%
Other 2 11%
Unknown 2 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 42%
Agricultural and Biological Sciences 6 32%
Computer Science 1 5%
Medicine and Dentistry 1 5%
Unknown 3 16%

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 09 October 2015.
All research outputs
#8,687,834
of 11,293,566 outputs
Outputs from BMC Bioinformatics
#3,314
of 4,195 outputs
Outputs of similar age
#154,585
of 247,049 outputs
Outputs of similar age from BMC Bioinformatics
#114
of 145 outputs
Altmetric has tracked 11,293,566 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,195 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 16th percentile – i.e., 16% 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 247,049 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 145 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.