Parsley: a web app for parsing data from plate readers

Abstract

Summary: As demand for the automation of biological assays has increased over recent years, the range of measurement types implemented by multiwell plate readers has broadened and the list of published software packages that caters to their analysis has grown. However, most plate readers export data in esoteric formats with little or no metadata, while most analytical software packages are built to work with tidy data accompanied by associated metadata. 'Parser' functions are therefore required to prepare raw data for analysis. Such functions are instrument- and data type-specific, and to date, no generic tool exists that can parse data from multiple data types or multiple plate readers, despite the potential for such a tool to speed up access to analysed data and remove an important barrier for less confident coders. We have developed the interactive web application, Parsley, to bridge this gap. Unlike conventional programmatic parser functions, Parsley makes few assumptions about exported data, instead employing user inputs to identify and extract data from data files. In doing so, it is designed to enable any user to parse plate reader data and can handle a wide variety of instruments (10+) and data types (53+). Parsley is freely available via a web interface, enabling access to its unique plate reader data parsing functionality, without the need to install software or write code.

Availability and implementation: The Parsley web application can be accessed at: https://gbstan.shinyapps.io/parsleyapp/. The source code is available at: https://github.com/ec363/parsleyapp and is archived on Zenodo: https://zenodo.org/records/10011752.

Figure 1.

The Parsley workflow. Screenshots of the Parsley app UI at three stages. (A) Raw Data and Metadata upload sections. (B) Data Specifications step 3: selection of first and last cells for the first reading using the interactive DataTables table. (C) The final Data Specifications step 7, in which the data, having been extracted in previous steps, is tidied and joined to the provided metadata, and can be downloaded as a CSV. The built parser function can then also be saved for reuse at a later date.