Delayed Fragmentation and Optimized Isolation Width Settings for Improvement of Protein Identification and Accuracy of Isobaric Mass Tag Quantification on Orbitrap-Type Mass Spectrometers

2011 ◽  
Vol 83 (23) ◽  
pp. 8959-8967 ◽  
Author(s):  
Mikhail M. Savitski ◽  
Gavain Sweetman ◽  
Manor Askenazi ◽  
Jarrod A. Marto ◽  
Manja Lang ◽  
...  
Keyword(s):  
Protein Identification ◽  
Mass Spectrometers ◽  
Type Mass ◽  
Mass Tag

scholarly journals Label-free quantification with FDR-controlled match-between-runs

2020 ◽  
Author(s):  
Fengchao Yu ◽  
Sarah E. Haynes ◽  
Alexey I. Nesvizhskii
Keyword(s):  
Protein Identification ◽  
Missing Values ◽  
Superior Performance ◽  
Label Free ◽  
Experimental Conditions ◽  
Mass Spectrometers ◽  
Tandem Mass Spectra ◽  
Label Free Quantification ◽  
Statistical Confidence ◽  
Free Quantification

AbstractMissing values weaken the power of label-free quantitative proteomic experiments to uncover true quantitative differences between biological samples or experimental conditions. Match-between-runs (MBR) has become a common approach to mitigate the missing value problem, where peptides identified by tandem mass spectra in one run are transferred to another by inference based on m/z, charge state, retention time, and ion mobility when applicable. Though tolerances are used to ensure such transferred identifications are reasonably located and meet certain quality thresholds, little work has been done to evaluate the statistical confidence of MBR. Here, we present a mixture model-based approach to estimate the false discovery rate (FDR) of peptide and protein identification transfer, which we implement in the label-free quantification tool IonQuant. Using several benchmarking datasets generated on both Orbitrap and timsTOF mass spectrometers, we demonstrate that IonQuant with FDR-controlled MBR results in superior performance compared to MaxQuant. We further illustrate the need for FDR-controlled MBR in sparse datasets such as those from single-cell proteomics experiments.

Charge permutation reactions in beam type mass spectrometers

2001 ◽  
Vol 212 (1-3) ◽  
pp. 219-227 ◽  
Author(s):  
Allison S. Danell ◽  
Gary L. Glish
Keyword(s):  
Mass Spectrometers ◽  
Beam Type ◽  
Type Mass

THE PROBABILITY DISTRIBUTION FOR A RANDOM MATCH BETWEEN AN EXPERIMENTAL-THEORETICAL SPECTRAL PAIR IN TANDEM MASS SPECTROMETRY

2005 ◽  
Vol 03 (02) ◽  
pp. 455-476 ◽  
Author(s):  
TEMA FRIDMAN ◽  
JANE RAZUMOVSKAYA ◽  
NATHAN VERBERKMOES ◽  
GREG HURST ◽  
VLADIMIR PROTOPOPESCU ◽  
...  
Keyword(s):  
Probability Distribution ◽  
Goodness Of Fit ◽  
Protein Identification ◽  
Scoring Function ◽  
Peptide Identification ◽  
Experimental Spectrum ◽  
Identification Problem ◽  
Theoretical Spectrum ◽  
Accurate Analysis ◽  
Mass Spectrometers

Proteomic techniques are fast becoming the main method for qualitative and quantitative determination of the protein content in biological systems. Despite notable advances, efficient and accurate analysis of high throughput proteomic data generated by mass spectrometers remains one of the major stumbling blocks in the protein identification problem. We present a model for the number of random matches between an experimental MS-MS spectrum and a theoretical spectrum of a peptide. The shape of the probability distribution is a function of the experimental accuracy, the number of peaks in the experimental spectrum, the length of the interval over which the peaks are distributed, and the number of theoretical spectral peaks in this interval. Based on this probability distribution, a goodness-of-fit tool can be used to yield fast and accurate scoring schemes for peptide identification through database search. In this paper, we describe one possible implementation of such a method and compare the performance of the resulting scoring function with that of SEQUEST. In terms of speed, our algorithm is roughly two orders of magnitude faster than the SEQUEST program, and its accuracy of peptide identification compares favorably to that of SEQUEST. Moreover, our algorithm does not use information related to the intensities of the peaks.

Solid Phase Isobaric Mass Tag Reagent for Simultaneous Protein Identification and Assay

2010 ◽  
Vol 82 (13) ◽  
pp. 5552-5560 ◽  
Author(s):  
Anna Napoli ◽  
Constantinos M. Athanassopoulos ◽  
Petros Moschidis ◽  
Donatella Aiello ◽  
Leonardo Di Donna ◽  
...  
Keyword(s):  
Protein Identification ◽  
Solid Phase ◽  
Mass Tag
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