five

Supporting data for "Keemei: cloud-based validation of tabular bioinformatics file formats in Google Sheets".

收藏
DataCite Commons2025-05-26 更新2025-04-15 收录
下载链接:
http://gigadb.org/dataset/100204
下载链接
链接失效反馈
官方服务:
资源简介:
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. <br> We present Keemei, a Google Sheets Add-on for validating tabular files used in bioinformatics analyses. Keemei is available free of charge from Googles 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. <br> 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.
提供机构:
GigaScience
创建时间:
2016-06-10
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作