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Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists

Overview of attention for article published in Genome Medicine, December 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
35 tweeters

Citations

dimensions_citation
56 Dimensions

Readers on

mendeley
208 Mendeley
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Title
Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists
Published in
Genome Medicine, December 2017
DOI 10.1186/s13073-017-0492-3
Pubmed ID
Authors

Xun Zhu, Thomas K. Wolfgruber, Austin Tasato, Cédric Arisdakessian, David G. Garmire, Lana X. Garmire

Abstract

Single-cell RNA sequencing (scRNA-Seq) is an increasingly popular platform to study heterogeneity at the single-cell level. Computational methods to process scRNA-Seq data are not very accessible to bench scientists as they require a significant amount of bioinformatic skills. We have developed Granatum, a web-based scRNA-Seq analysis pipeline to make analysis more broadly accessible to researchers. Without a single line of programming code, users can click through the pipeline, setting parameters and visualizing results via the interactive graphical interface. Granatum conveniently walks users through various steps of scRNA-Seq analysis. It has a comprehensive list of modules, including plate merging and batch-effect removal, outlier-sample removal, gene-expression normalization, imputation, gene filtering, cell clustering, differential gene expression analysis, pathway/ontology enrichment analysis, protein network interaction visualization, and pseudo-time cell series construction. Granatum enables broad adoption of scRNA-Seq technology by empowering bench scientists with an easy-to-use graphical interface for scRNA-Seq data analysis. The package is freely available for research use at http://garmiregroup.org/granatum/app.

Twitter Demographics

The data shown below were collected from the profiles of 35 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 208 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Unknown 207 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 57 27%
Student > Ph. D. Student 47 23%
Student > Master 22 11%
Student > Bachelor 16 8%
Professor 7 3%
Other 23 11%
Unknown 36 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 60 29%
Agricultural and Biological Sciences 49 24%
Computer Science 16 8%
Neuroscience 10 5%
Medicine and Dentistry 8 4%
Other 19 9%
Unknown 46 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 36. 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 26 March 2021.
All research outputs
#839,327
of 20,582,425 outputs
Outputs from Genome Medicine
#168
of 1,330 outputs
Outputs of similar age
#26,076
of 438,049 outputs
Outputs of similar age from Genome Medicine
#23
of 100 outputs
Altmetric has tracked 20,582,425 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,330 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.5. This one has done well, scoring higher than 87% 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 438,049 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 94% of its contemporaries.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.