R Shiny App for Standardized Detection of Outliers in Bioassay Development

The availability of reliable and sensitive assays is an important building block in the production and quality control of biological products. In the development of such assays, unusual or erroneous measurement results need to be detected, but adjudication by human operators is often inconsistent or prone to bias.

To help overcome this challenge, a Shiny app for the statistical detection of such outliers is being developed at Staburo: the Optimal Tool for Tracking of Outliers (OTTO). Close collaboration with the end users throughout the development process ensures that the statistical outlier detection results are in good agreement with subject matter expert evaluations. In particular, a mixed method approach was chosen which significantly reduced false outlier detection rates, compared to conventional statistical methods.

Thanks to the capabilities of the R Shiny technology, the user interface is intuitive and well suited for everyday use in the lab. Features of the app include application of outlier tests, automatic curve refitting after removal of outliers, and report generation for documentation purposes.

Data analysis, clinical biostatistics and more.