Background

midiaPASEF is a novel Data-Independent Acquisition (DIA) method implemented on Bruker timsTOF devices.
midiaPASEF offers the benefit of recording the precursor origins of fragment measurements.
Due to its novelty, the method's advantages cannot be fully utilized with existing data analysis solutions.
Therefore, we present midiaID: a flexible pipeline for the analysis of midiaPASEF data.

Methods

midiaID is a multistep procedure organized into a Snakemake pipeline.
This allows for easy investigation of different pipeline setups, optimization, and scalability depending on the hardware used.

The pipeline proceeds along the following lines:
1. Precursor and fragment data is clustered
2. For each fragment cluster we predict its precursor position roughly matching it with potential precursors.
3. Obtained fragment-precursor matches intensity patterns are compared and unlikely matches filtered out.
4. Data is then cast into an MGF format and searched with a DDA search engine, SAGE.
5. Search results are mapped back to the original graph, allowing for recalibration of measured quantities and the training of machine learning model for edge quality assessment.
6. Low scoring edges are filtered out and remaining one are searched again and findings rescored.

The two-searches approach allow cleaning of the precursor-fragment graph, providing the search engine with less noisy spectra and thus -- enhancing the quality of matches.

Conclusions

midiaID is a flexible and scalable pipeline for the analysis of midiaPASEF data.