A key step in understanding the results of biological experiments is visualization of the data. Many laboratory experiments contain a range of measurements that exist within a hierarchy of interdependence. An automated and facile way to visualize and interrogate such multilevel data, across many experimental variables, would (i) lead to improved understanding of the results, (ii) help to avoid misleading interpretation of statistics and (iii) easily identify outliers and sources of batch and confounding effects. While many excellent graphing solutions already exist, they are often geared towards the production of publication-ready plots and the analysis of a single variable at a time, require programming expertise or are unnecessarily complex for the task at hand. Here, we present Laboratory Automated Interrogation of Data (LAB-AID), an interactive tool specifically designed to automatically visualize and query hierarchical data resulting from biological experiments.
Keywords: R Shiny; automatization; data; statistics; visualization.
© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.