dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts.
Vadim DemichevLukasz SzyrwielFengchao YuGuo Ci TeoGeorge A RosenbergerAgathe NiewiendaDaniela LudwigJens DeckerStephanie Kaspar-SchoenefeldKathryn S LilleyMichael MüllederAlexey I NesvizhskiiMarkus RalserPublished in: Nature communications (2022)
The dia-PASEF technology uses ion mobility separation to reduce signal interferences and increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-picking algorithm and generation of optimized spectral libraries, as well as take advantage of neural network-based processing of dia-PASEF data. Our computational platform boosts proteomic depth by up to 83% compared to previous work, and is specifically beneficial for fast proteomic experiments and those with low sample amounts. It quantifies over 5300 proteins in single injections recorded at 200 samples per day throughput using Evosep One chromatography system on a timsTOF Pro mass spectrometer and almost 9000 proteins in single injections recorded with a 93-min nanoflow gradient on timsTOF Pro 2, from 200 ng of HeLa peptides. A user-friendly implementation is provided through the incorporation of the algorithms in the DIA-NN software and by the FragPipe workflow for spectral library generation.
Keyphrases
- neural network
- optical coherence tomography
- label free
- electronic health record
- machine learning
- big data
- deep learning
- anti inflammatory
- healthcare
- primary care
- liquid chromatography
- ultrasound guided
- high resolution
- platelet rich plasma
- data analysis
- magnetic resonance imaging
- high speed
- quality improvement
- low cost
- signaling pathway