Analysis of tandem mass spectrometry data with CONGA: Combining Open and Narrow searches with Group-wise Analysis

Abstract

Searching 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 spectrums precursor mass differs from the peptide mass. However, expanding the search space in this way can lead to a loss in statistical power to detect peptides. We therefore developed a method, called CONGA, 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 (FDR) 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.