Parsley: a web app for parsing data from plate readers.

Area of Science:

• Biotechnology
• Bioinformatics
• Scientific Software Development

Background:

• Automation in biological assays has increased, leading to broader measurement types in multiwell plate readers.
• Most plate readers export data in proprietary formats lacking metadata, hindering analysis with standard software.
• Existing data parsing tools are instrument- and data type-specific, lacking a universal solution.

Purpose of the Study:

• To develop a generic, user-friendly tool for parsing data from diverse multiwell plate readers and data types.
• To bridge the gap between raw experimental data and analysis-ready formats.
• To reduce barriers for researchers, especially those less experienced with coding, in accessing analyzed biological assay data.

Main Methods:

• Development of an interactive web application named Parsley.
• Parsley employs user inputs to identify and extract data, making minimal assumptions about exported file formats.
• The application supports a wide range of instruments (10+) and data types (53+).

Main Results:

• Parsley successfully parses data from multiple plate reader instruments and diverse data types.
• The web application requires no software installation or coding knowledge from the user.
• It provides a significant improvement in accessing and preparing biological assay data for analysis.

Conclusions:

• Parsley offers a universal solution for parsing multiwell plate reader data, enhancing accessibility and efficiency in biological research.
• The tool democratizes data analysis by enabling users of all skill levels to process complex experimental outputs.
• Freely available online, Parsley accelerates the path from data generation to meaningful scientific insights.