Improvements in Automated Quantitation

Presenter highlights improvements to the in silico quantification workflow, enhancing peak detection, signal processing, and automated bounding, reducing manual effort and improving data accuracy.

Webinar Summary

This webinar covers the enhancements within Byos’ automated quantification pipeline and in-silico workflows, particularly focusing on the challenges and improvements in handling complex peptide identifications and quantifications. Gary Wilson discusses the design of the in-silico workflow, which allows for the extension of analytical results to future samples through the exportation of results in a CSV format. This includes detailed information such as peptide sequences, modifications, and charge states. The benefits of this approach are highlighted, particularly its utility in MS1-only level analysis, which supports instruments without MS2 capabilities.

Specific pain points previously encountered in the workflow, such as inconsistencies in peak capture and bounding in chromatographic runs, are also covered. Improvements include advanced signal processing techniques and a refined segmentation algorithm that enhances the accuracy of start and end times in peak detection. These technical enhancements facilitate better handling of deamidated peptides and other challenging variants, achieving near-baseline resolution in complex mixtures. The webinar concludes with a discussion on additional upgrades like automated retention time adjustments and charge state alignments, which simplify user interactions with the software and improve overall analytical outcomes. These advancements are part of the software’s latest release, aiming to streamline processes and increase the reliability of results in proteomic analysis.