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Title: Supporting data for "Keemei: cloud-based validation of tabular bioinformatics file formats in Google Sheets"      
dateReleased:
06-10-2016
privacy:
not applicable
aggregation:
instance of dataset
dateCreated:
06-10-2016
refinement:
curated
ID:
doi:10.5524/100204
creators:
Rideout, Jai Ram
Chase, John H
Boylen, Evan
Ackermann, Gail
Gonzalez, Antonio
Knight, Rob
,
availability:
available
types:
sequence
description:
Bioinformatics software often requires human-generated tabular text files as input and have 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 concurrent editing of a single spreadsheet by different users working on different platforms. Often most of the researchers who are entering data will not be 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 validation of two widely used tabular bioinformatics formats, the QIIME sample metadata mapping file format, and the Spatially Referenced Genetic Data (SRGD) format, but is designed to easily support the addition of others. Included in this GigaDB dataset are the archival code and test data as reviewed at the time of publication, for the most recent version of the application please visit the Keemei website.
accessURL: https://doi.org/10.5524/100204
storedIn:
GigaScience
qualifier:
not compressed
format:
HTML
accessType:
landing page
primary:
true
authentication:
none
authorization:
none
abbreviation:
GigaDB
homePage: http://gigadb.org/
ID:
SCR:006565
name:
Giga Science Database

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