Quality control (QC) strategies for monitoring and assessing instrument performance during mass spectrometry analysis is crucial for ensuring that the data generated is high-quality, reproducible, and accurate.
Quality control (QC) strategies for monitoring and assessing instrument performance during mass spectrometry analysis is crucial for ensuring that the data generated is high-quality, reproducible, and accurate.
Particularly for metabolomics and lipidomics, traditional QC approaches often involve manual inspection of the data, which is time-consuming, subjective, prone to human error, and not viable for high-throughput studies with hundreds of samples.
A team of scientists from Pacific Northwest National Laboratory (PNNL) and the Environmental Molecular Sciences Laboratory (EMSL) have developed PeakQC, a new software tool for automated quality control of mass spectrometry data.
The findings are published in the Journal of the American Society for Mass Spectrometry.
Unlike existing QC tools that focus on specific types of molecules, PeakQC can analyze data from various “omics” fields, like proteomics, metabolomics, and lipidomics.
