Fig. 1: DIAMetAlyzer - a pipeline for assay library generation and targeted analysis with statistical validation. | Nature Communications

Fig. 1: DIAMetAlyzer - a pipeline for assay library generation and targeted analysis with statistical validation.

From: DIAMetAlyzer allows automated false-discovery rate-controlled analysis for data-independent acquisition in metabolomics

Fig. 1: DIAMetAlyzer - a pipeline for assay library generation and targeted analysis with statistical validation.The alternative text for this image may have been generated using AI.

DDA data is used for candidate identification containing feature detection, adduct grouping and accurate mass search. Library construction uses fragment annotation via compositional fragmentation trees (SIRIUS) and decoy generation using a fragmentation tree re-rooting method (Passatutto) to create a target-decoy assay library. This library is used in a second step to analyse metabolomics DIA data by performing targeted extraction (OpenSWATH), scoring and statistical validation (PyProphet).

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