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Reputable Mentor II
Reputable Mentor II
Frank Berg1; Carmen Paschke1; Kai Fritzemeier1; Pedro Navarro1, Torsten Ueckert1; David Horn2; Bernard Delanghe1
ASMS 2019 Poster
Purpose: Implement an easy-to-use mechanism to enrich workflows with results of non-C# user algorithms in Thermo Scientific™ Proteome Discoverer™ framework. Methods: Creating a family of preconfigured nodes as well as general mechanisms that integrate the calculation results of arbitrary external executables or scripts into Thermo Scientific™ Proteome Discoverer™ 2.4 software result files. Results: We show by means of a custom R script that employs the widely used limma package [1] the integration of its results into Thermo Scientific™ Proteome Discoverer™ 2.4 software and use the additional statistical results of quantification data to compare them to the built-in Thermo Scientific™ Proteome Discoverer™ 2.4 software statistics algorithms. For this we use the rich set of plots and table presentations in Thermo Scientific™ Proteome Discoverer™ 2.4 software as well as R Studio.


1. Thermo Fisher Scientific (Bremen) GmbH, Bremen, Germany 2. Thermo Fisher, San Jose, CA
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‎10-15-2021 11:31 AM
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