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Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry
Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry
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Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry
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Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry
Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry

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Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry
Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry
Journal Article

Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry

2018
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Overview
Data independent acquisition (DIA) mass spectrometry is a powerful technique that is improving the reproducibility and throughput of proteomics studies. Here, we introduce an experimental workflow that uses this technique to construct chromatogram libraries that capture fragment ion chromatographic peak shape and retention time for every detectable peptide in a proteomics experiment. These coordinates calibrate protein databases or spectrum libraries to a specific mass spectrometer and chromatography setup, facilitating DIA-only pipelines and the reuse of global resource libraries. We also present EncyclopeDIA, a software tool for generating and searching chromatogram libraries, and demonstrate the performance of our workflow by quantifying proteins in human and yeast cells. We find that by exploiting calibrated retention time and fragmentation specificity in chromatogram libraries, EncyclopeDIA can detect 20–25% more peptides from DIA experiments than with data dependent acquisition-based spectrum libraries alone. Data-independent acquisition (DIA)-based proteomics often relies on mass spectrum libraries from data-dependent acquisition experiments. Here, the authors present a method to generate DIA-based chromatogram libraries, enabling DIA-only workflows and detecting more peptides than with spectrum libraries alone.