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RNASeqMetaDB: a database and web server for navigating metadata of publicly available mouse RNA-Seq datasets

Overview of attention for article published in Bioinformatics, August 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
5 X users

Readers on

mendeley
37 Mendeley
citeulike
3 CiteULike
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Article details
Title
RNASeqMetaDB: a database and web server for navigating metadata of publicly available mouse RNA-Seq datasets
Published in
Bioinformatics, August 2015
DOI 10.1093/bioinformatics/btv503
Pubmed ID
Authors

Zhengyu Guo, Boriana Tzvetkova, Jennifer M Bassik, Tara Bodziak, Brianna M Wojnar, Wei Qiao, Md A Obaida, Sacha B Nelson, Bo Hua Hu, Peng Yu

Abstract

Gene targeting is a protocol for introducing a mutation to a specific gene in an organism. Because of the importance of in vivo assessment of gene function and modeling of human diseases, this technique has been widely adopted to generate a large number of mutant mouse models. Due to the recent breakthroughs in high-throughput sequencing technologies, RNA-Seq experiments have been performed on many of these mouse models, leading to hundreds of publicly available data sets. To facilitate the reuse of these data sets, we collected the associated metadata and organized them in a database called RNASeqMetaDB. The metadata was manually curated to ensure annotation consistency. We developed a web server to allow easy database navigation and data querying. Users can search the database using multiple parameters like genes, diseases, tissue types, keywords, and associated publications in order to find data sets that match their interests. Summary statistics of the metadata is also presented on the web server showing interesting global patterns of RNA-Seq studies. Freely available on the web at http://rnaseqmetadb.ece.tamu.edu. [email protected] information.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 5%
Germany 2 5%
Hungary 1 3%
France 1 3%
China 1 3%
Unknown 30 81%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 11 30%
Researcher 11 30%
Other 3 8%
Student > Master 3 8%
Student > Bachelor 2 5%
Other 3 8%
Unknown 4 11%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 14 38%
Computer Science 8 22%
Biochemistry, Genetics and Molecular Biology 7 19%
Physics and Astronomy 1 3%
Chemistry 1 3%
Other 0 0%
Unknown 6 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 15 December 2015.
All research outputs
#2,531,794
of 28,833,811 outputs
Outputs from Bioinformatics
#1,558
of 13,312 outputs
Outputs of similar age
#29,531
of 280,713 outputs
Outputs of similar age from Bioinformatics
#58
of 178 outputs
Altmetric has tracked 28,833,811 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,312 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 88% 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 280,713 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 89% of its contemporaries.
We're also able to compare this research output to 178 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.