A noise model for mass spectrometry based proteomics

Du, Pan; Stolovitzky, Gustavo; Horvatovich, Péter; Bischoff, Rainer; J, Lim; Suits, Frank

doi:10.1093/bioinformatics/btn078

Cited by 66 publications

(76 citation statements)

References 22 publications

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“…We also developed a robust error model that allows estimation of p value, q value, and confidence interval on any measured iTRAQ ratio from a single experiment. Our approach represents a paradigm shift relative to previous methodologies for quantitative proteomics in that we derive a parametric error model from a large number of weak variance estimates (49), all within a single acquisition, rather than extensive, empirical characterization of individual mass spectrometry peaks (20,33,34,50). The ability of our model, developed herein for LC-MS/MS analysis of iTRAQ-labeled peptides on an Orbitrap, to provide improved estimates of precision for data acquired some two decades ago on small molecules ionized by electron impact and analyzed in MS mode on an FT/ICR mass spectrometer strongly supports the validity of our approach.…”

Section: Direct Comparison Of Constitutively Active Flt3 Mutants Suggmentioning

confidence: 99%

A Robust Error Model for iTRAQ Quantification Reveals Divergent Signaling between Oncogenic FLT3 Mutants in Acute Myeloid Leukemia

Zhang

Askenazi

Jiang

et al. 2010

Molecular & Cellular Proteomics

105

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The FLT3 receptor tyrosine kinase plays an important role in normal hematopoietic development and leukemogenesis. Point mutations within the activation loop and inframe tandem duplications of the juxtamembrane domain represent the most frequent molecular abnormalities observed in acute myeloid leukemia. Interestingly these gain-of-function mutations correlate with different clinical outcomes, suggesting that signals from constitutive FLT3 mutants activate different downstream targets. In principle, mass spectrometry offers a powerful means to quantify protein phosphorylation and identify signaling events associated with constitutively active kinases or other oncogenic events. However, regulation of individual phosphorylation sites presents a challenging case for proteomics studies whereby quantification is based on individual peptides rather than an average across different peptides derived from the same protein. Here we describe a robust experimental framework and associated error model for iTRAQ-based quantification on an Orbitrap mass spectrometer that relates variance of peptide ratios to mass spectral peak height and provides for assignment of p value, q value, and confidence interval to every peptide identification, all based on routine measurements, obviating the need for detailed characterization of individual ion peaks. Moreover, we demonstrate that our model is stable over time and can be applied in a manner directly analogous to ubiquitously used external mass calibration routines. Application of our error model to quantitative proteomics data for FLT3 signaling provides evidence that phosphorylation of tyrosine phosphatase SHP1 abrogates the transformative potential, but not overall kinase activity, of FLT3-D835Y in acute myeloid leukemia. Molecular & Cellular Proteomics 9:780 -790, 2010.Deregulated tyrosine phosphorylation is a well established molecular hallmark in the development of both solid tumors and hematopoietic malignancies (1, 2). In acute myeloid leukemia (AML), 1 mutations of the Fms-like tyrosine kinase 3 (Flt3) gene or its overexpression represent the most frequent molecular abnormalities, observed in ϳ35 and ϳ90% of patients, respectively (3, 4). Internal tandem duplication (ITD) in the juxtamembrane region occurs in ϳ25% of patients, whereas another 7% of cases manifest as point mutations in the activation loop at Asp-835 (typically D835Y). Both mutation classes induce constitutive tyrosine kinase activity and confer IL-3-independent growth of the factor IL-3-dependent BaF3 and 32D cells. Interestingly, the ITD and D835Y mutants respond differently to the current suite of targeted therapeutics (5), and in vitro studies suggest that they can activate different downstream targets, including STAT5a (6 -8). Collectively, these observations motivate continued efforts to delineate oncogenic pathways in further detail to expand our understanding of the molecular basis for disease progression and to identify additional therapeutic entry points.Over the past decade, mass spectrometry-based pr...

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Section: Direct Comparison Of Constitutively Active Flt3 Mutants Suggmentioning

confidence: 99%

A Robust Error Model for iTRAQ Quantification Reveals Divergent Signaling between Oncogenic FLT3 Mutants in Acute Myeloid Leukemia

Zhang

Askenazi

Jiang

et al. 2010

Molecular & Cellular Proteomics

105

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“…We therefore model the noise contamination with multiplicative noise, which standard deviation is proportional to the value of eacg signal coefficient. Numerous studies have come to similar conclusions [12], [13]. Considering that the noise is a mixture of an additive component and a multiplicative component yields the following model for the standard deviation of the noise on each coefficient of the data:…”

Section: B About the Noise Contaminationmentioning

confidence: 71%

“…Zooming on the main peak of the previous figure yields Fig. 2b, where a small peak is visible at +1Da, which is typical of the presence of carbon-13 13 C. This figure also highlights the large range of intensities which must be extracted from the data. In practice, the main peak has a width of about ten samples, showing the extreme precision of the Orbitrap spectrometer which was used for the acquisition of these data.…”

Section: A Mass and Elution Profilesmentioning

confidence: 74%

Application of non-negative matrix factorization to LC/MS data

et al. 2016

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Abstract-LiquidChromatography-Mass Spectrometry (LC/MS) provides large datasets from which one needs to extract the relevant information. Since these data are made of non-negative mixtures of non-negative mass spectra, nonnegative matrix factorization (NMF) is well suited for its processing, but it has barely been used in LC/MS. Also, these data are very difficult to deal with since they are usually contaminated with non-Gaussian noise and the intensities vary on several orders of magnitude. In this article, we show the feasibility of the NMF approach on these data. We also propose an adaptation of one of the algorithms aiming at specifically dealing with LC/MS data. We finally perform experiments and compare standard NMF algorithms on both simulated data and an annotated LC/MS dataset. This lets us evaluate the influence of the noise model and the data model on the recovery of the sources.

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“…Some types of mass spectrometry have Poisson-distributed noise as well, although the noise distribution is often complex; while this model may be a suitable estimate of the noise in mass spectrometry, this would have to be investigated further. [5] The focus of the smoothing method presented in this article is on Raman spectroscopy, since the authors have ready access to an FT-Raman system, but, as noted above, the method is believed to be applicable to other spectroscopic techniques as well. Raman spectra contain noise contributions that are both homoscedastic (noise is independent of the signal intensity) and heteroscedastic (the noise is dependent on the signal intensity).…”

Section: Introductionmentioning

confidence: 99%

Denoising of spectra with no user input: a spline‐smoothing algorithm

Rowlands

Elliott

2011

J Raman Spectroscopy

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A new method has been developed for denoising a spectrum using cubic-spline smoothing, which requires no user input or judgement, yet outperforms other more conventional algorithms. It relies only on the assumptions that the spectrum is sampled at a resolution much higher than the full-width at half maximum of any peaks, and that the noise is approximately Gaussian distributed, although any other type of noise distribution is acceptable so long as the type of distribution is known. Copyright

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A noise model for mass spectrometry based proteomics

Cited by 66 publications

References 22 publications

A Robust Error Model for iTRAQ Quantification Reveals Divergent Signaling between Oncogenic FLT3 Mutants in Acute Myeloid Leukemia

A Robust Error Model for iTRAQ Quantification Reveals Divergent Signaling between Oncogenic FLT3 Mutants in Acute Myeloid Leukemia

Application of non-negative matrix factorization to LC/MS data

Denoising of spectra with no user input: a spline‐smoothing algorithm

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