Keemei: cloud-based validation of tabular bioinformatics file formats in Google Sheets.
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.
Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, 86011, USA.
Jai Ram
JR
Rideout
Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, 86011, USA.
John H
JH
Chase
Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, 86011, USA.
Evan
E
Bolyen
Department of Pediatrics, University of California San Diego, San Diego, CA, 92093, USA.
Gail
G
Ackermann
Department of Pediatrics, University of California San Diego, San Diego, CA, 92093, USA.
Antonio
A
González
Department of Pediatrics, University of California San Diego, San Diego, CA, 92093, USA.|Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, 92093, USA.
Rob
R
Knight
Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, 86011, USA. gregcaporaso@gmail.com.|Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, 86011, USA. gregcaporaso@gmail.com.
J Gregory
JG
Caporaso
D000067917:Cloud Computing; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D016247:Information Storage and Retrieval; D012984:Software; D014584:User-Computer Interface
Cloud; Data validation; Metadata; Plugin; QIIME; Spreadsheet; Tabular file format