Analysis of Tandem Mass Spectrometry Data with CONGA: Combining Open and Narrow Searches with Group-Wise Analysis.
Jack FreestoneWilliam Stafford NobleUri KeichPublished in: Journal of proteome research (2024)
Searching for tandem mass spectrometry proteomics data against a database is a well-established method for assigning peptide sequences to observed spectra but typically cannot identify peptides harboring unexpected post-translational modifications (PTMs). Open modification searching aims to address this problem by allowing a spectrum to match a peptide even if the spectrum's precursor mass differs from the peptide mass. However, expanding the search space in this way can lead to a loss of statistical power to detect peptides. We therefore developed a method, called CONGA (combining open and narrow searches with group-wise analysis), that takes into account results from both types of searches─a traditional "narrow window" search and an open modification search─while carrying out rigorous false discovery rate control. The result is an algorithm that provides the best of both worlds: the ability to detect unexpected PTMs without a concomitant loss of power to detect unmodified peptides.
Keyphrases
- tandem mass spectrometry
- ultra high performance liquid chromatography
- high performance liquid chromatography
- liquid chromatography
- gas chromatography
- simultaneous determination
- minimally invasive
- mass spectrometry
- solid phase extraction
- electronic health record
- high resolution mass spectrometry
- small molecule
- machine learning
- amino acid
- emergency department
- big data
- artificial intelligence
- ms ms