Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics.

Nat Methods
Authors
Keywords
Abstract

Mass spectrometry with data-independent acquisition (DIA) is a promising method to improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory by systematically measuring all peptide precursors in a biological sample. However, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms (SNPs) and alternative site localizations in phosphoproteomics data. We report Specter (https://github.com/rpeckner-broad/Specter), an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly through comparison to a spectral library, thus circumventing the problems associated with typical fragment-correlation-based approaches. We validate the sensitivity of Specter and its performance relative to that of other methods, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.

Year of Publication
2018
Journal
Nat Methods
Volume
15
Issue
5
Pages
371-378
Date Published
2018 05
ISSN
1548-7105
DOI
10.1038/nmeth.4643
PubMed ID
29608554
PubMed Central ID
PMC5924490
Links
Grant list
U54 HG008097 / HG / NHGRI NIH HHS / United States