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Keemei: cloud-based validation of tabular bioinformatics file formats in Google Sheets

Overview of attention for article published in Giga Science, June 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)

Mentioned by

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9 X users
peer_reviews
1 peer review site
facebook
1 Facebook page

Citations

dimensions_citation
33 Dimensions

Readers on

mendeley
107 Mendeley
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2 CiteULike
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Title
Keemei: cloud-based validation of tabular bioinformatics file formats in Google Sheets
Published in
Giga Science, June 2016
DOI 10.1186/s13742-016-0133-6
Pubmed ID
Authors

Jai Ram Rideout, John H. Chase, Evan Bolyen, Gail Ackermann, Antonio González, Rob Knight, J. Gregory Caporaso

Abstract

Bioinformatics software often requires human-generated tabular text files as input and has specific requirements for how those data are formatted. Users frequently manage these data in spreadsheet programs, which is convenient for researchers who are compiling the requisite information because the spreadsheet programs can easily be used on different platforms including laptops and tablets, and because they provide a familiar interface. It is increasingly common for many different researchers to be involved in compiling these data, including study coordinators, clinicians, lab technicians and bioinformaticians. As a result, many research groups are shifting toward using cloud-based spreadsheet programs, such as Google Sheets, which support the concurrent editing of a single spreadsheet by different users working on different platforms. Most of the researchers who enter data are not familiar with the formatting requirements of the bioinformatics programs that will be used, so validating and correcting file formats is often a bottleneck prior to beginning bioinformatics analysis. We present Keemei, a Google Sheets Add-on, for validating tabular files used in bioinformatics analyses. Keemei is available free of charge from Google's Chrome Web Store. Keemei can be installed and run on any web browser supported by Google Sheets. Keemei currently supports the validation of two widely used tabular bioinformatics formats, the Quantitative Insights into Microbial Ecology (QIIME) sample metadata mapping file format and the Spatially Referenced Genetic Data (SRGD) format, but is designed to easily support the addition of others. Keemei will save researchers time and frustration by providing a convenient interface for tabular bioinformatics file format validation. By allowing everyone involved with data entry for a project to easily validate their data, it will reduce the validation and formatting bottlenecks that are commonly encountered when human-generated data files are first used with a bioinformatics system. Simplifying the validation of essential tabular data files, such as sample metadata, will reduce common errors and thereby improve the quality and reliability of research outcomes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hong Kong 1 <1%
United States 1 <1%
Brazil 1 <1%
Unknown 104 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 18%
Student > Ph. D. Student 18 17%
Researcher 13 12%
Student > Bachelor 12 11%
Student > Postgraduate 6 6%
Other 15 14%
Unknown 24 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 27%
Biochemistry, Genetics and Molecular Biology 20 19%
Immunology and Microbiology 7 7%
Computer Science 6 6%
Engineering 5 5%
Other 12 11%
Unknown 28 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 12 July 2019.
All research outputs
#5,216,578
of 25,394,764 outputs
Outputs from Giga Science
#812
of 1,168 outputs
Outputs of similar age
#86,911
of 368,606 outputs
Outputs of similar age from Giga Science
#12
of 14 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,168 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.8. This one is in the 30th percentile – i.e., 30% 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 368,606 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 76% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.