Plant hormones are compounds that regulate plant growth and their levels provide very important information for plant researchers. We have created an LC-MS/MS method that simultaneously quantifies 30 hormone analytes using 20 internal standards.  Measuring and processing these 50 signals is complicated and becomes a bottleneck, slowing workflow. Current commercially available software is costly and inflexible to the dynamic needs of analyses of this type.  Previously we relied on MS-Excel to perform the calculations and generate 30 standard curves, which is time consuming and error prone.  A software tool was developed to improve the analysis of hormone data sets using R/Shiny/PostgreSQL.  This tool allows users to import data from the instrument and automatically calculates hormone concentrations in each sample.  Users have full access to inspect and remove outlier data points as appropriate. This application has dramatically reduced hormone data analysis times by 85% (3 days to about 3 hours for one plate of data).

Robust, automated hormone data analysis

254th National Meeting (2017)

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