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ABSTRACT: Introduction
We have developed a set of tools built with open-source software that includes both a database and a visualization component to collect LC-MS/MS data and monitor quality control parameters.Description of tool
To display LC-MS/MS data we built a parsing tool using Python and standard libraries to parse the XML files after each clinical run. The tool parses the necessary information to store a database comprised of three distinct tables. Another component to this toolkit is an interactive data visualization tool that uses the data from the database. There are 5 different visualizations that present the data based on interchangeable parameters.Evaluation of tool
Using histogram visualization, we assessed how quality control parameters that feed our quality
SUBMITTER: Pablo A
PROVIDER: S-EPMC8739458 | biostudies-literature | 2022 Jan
REPOSITORIES: biostudies-literature