A guided tour of the Trans‐Proteomic Pipeline

Deutsch, Eric W.; Mendoza, Luis; Shteynberg, David; Farrah, Terry; Lam, Henry; Tasman, Natalie; Sun, Zhi; Nilsson, Erik; Pratt, Brian; Prazen, Bryan J.; Eng, Jimmy K.; Martin, Daniel; Nesvizhskii, Alexey I.; Aebersold, Ruedi

doi:10.1002/pmic.200900375

Cited by 728 publications

(634 citation statements)

References 48 publications

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“…The OpenMS project is one of multiple software solutions addressing the computational challenges of mass spectrometry-based proteomics, each contributing in different areas such as protein inference, peptide database search or file conversion [6,7,23,24] . While some proprietary software packages offer solutions for specialized use cases, their closed nature makes their adaption to new requirements and integration into more complex workflows difficult.…”

Section: Community-driven Developmentmentioning

confidence: 99%

“…Past efforts to mitigate these issues have led to the development of standardized data exchange formats [2,3,4,5] , which have recently been adopted by several software projects [6,7,8,9,10] . These standard formats enable the integration of tools from different sources, simplify the analysis of MS data from multiple vendors, and render published results more readily accessible.…”

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OpenMS: a flexible open-source software platform for mass spectrometry data analysis

et al. 2016

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Section: Community-driven Developmentmentioning

confidence: 99%

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OpenMS: a flexible open-source software platform for mass spectrometry data analysis

et al. 2016

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“…Libraries are shown to be much faster and capable of identifying low-quality spectra than sequence search engines, 2 as they search a smaller space (fewer candidates to choose from) and use real reference spectra with known ion intensities as opposed to simplistically predicted intensities in the sequence search engines. 29 The lowquality spectra of the early developmental stages (1 and 2 dpf) therefore might have been expected to perform so much better when searching against the library than against the sequence database ( Figure 4). For all developmental stages, larger numbers of spectra could be identified using SpectraST and the A library, than using SpectraST and the embryo-derived library or an X!Tandem sequence database search.…”

Section: Organ Differentiated Zebrafish Spectral Librarymentioning

confidence: 99%

Identifying Proteins in Zebrafish Embryos Using Spectral Libraries Generated from Dissected Adult Organs and Tissues

et al. 2014

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Spectral libraries provide a sensitive and accurate method for identifying peptides from tandem mass spectra, complementary to searching genome-derived databases or sequencing de novo. Their application requires comprehensive libraries including peptides from low-abundant proteins. Here we describe a method for constructing such libraries using biological differentiation to "fractionate" the proteome by harvesting adult organs and tissues and build comprehensive libraries for identifying proteins in zebrafish (Danio rerio) embryos and larvae (an important and widely used model system). Hierarchical clustering using direct comparison of spectra was used to prioritize organ selection. The resulting and publicly available library covers 14 164 proteins, significantly improved the number of peptide-spectrum matches in zebrafish developmental stages, and can be used on data from different instruments and laboratories. The library contains information on tissue and organ expression of these proteins and is also applicable for adult experiments. The approach itself is not limited to zebrafish but would work for any model system.

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“…The statistics for assessing identification data, whether evaluating individual peptidespectrum matches (32,42,50), stratifying confident identifications from likely errors across an LC-MS/MS file (40,51,52), or computing probabilities associated with proteins and isoforms (53)(54)(55), are key to discerning the value of these findings. Combining identifications from multiple search engines to more broadly interrogate the MS/MS data is commonly performed by software tools such as PEAKS inChorus (Bioinformatics Solutions Inc.), Phenyx (GeneBio), Proteome Software's Scaffold (56), and the Trans-Proteomic Pipeline's iProphet (57). A wide variety of tools adds more biological context to the list of identified proteins; a small sample of these include ProteinCenter (Thermo Fischer Scientific), Kyoto Encyclopedia of Genes and Genomes (58), PANTHER Classification System (59), Cytoscape (60), and WebGestalt (61).…”

Section: Figmentioning

confidence: 99%

A Face in the Crowd: Recognizing Peptides Through Database Search

Eng

Searle²,

Clauser

et al. 2011

Molecular & Cellular Proteomics

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Peptide identification via tandem mass spectrometry sequence database searching is a key method in the array of tools available to the proteomics researcher. The ability to rapidly and sensitively acquire tandem mass spectrometry data and perform peptide and protein identifications has become a commonly used proteomics analysis technique because of advances in both instrumentation and software. Although many different tandem mass spectrometry database search tools are currently available from both academic and commercial sources, these algorithms share similar core elements while maintaining distinctive features. This review revisits the mechanism of sequence database searching and discusses how various parameter settings impact the underlying search. Molecular & Cellular Proteomics 10: 10.1074/ mcp.R111.009522, 1-9, 2011.Innovations in tandem mass spectrometry (MS/MS) 1 have enabled the rapid growth of proteomics for chemists and biologists alike. In addition to the evolution of the instrument hardware to acquire spectra more rapidly and sensitively, improvements to data analysis facilitates the process of identifying and quantifying peptides and proteins for a wide user base. Researchers new to the field can benefit from a review of the fundamentals of tandem mass spectrometry sequence database searching, and even experienced proteomics researchers may profit from considerations of practical strategies to maximize information extraction from data.In a typical shotgun proteomics experiment, the sample is first denatured to enable proteolysis. An enzyme such as trypsin is applied to cleave proteins to smaller peptide components. This peptide mixture is usually then separated on a liquid chromatography (LC) column; more complex samples may necessitate prior fractionation by strong cation exchange or isoelectric focusing. Peptides are subjected to ionizing voltage as they are electrosprayed from the column, and these ions are introduced into the near-vacuum environment of the mass spectrometer.In a tandem mass spectrometry experiment, the instrument will first acquire a survey or precursor scan, also referred to as an MS scan, which measures all intact peptide ions eluting into the mass spectrometer at that given time. One or more peptide ions are selected, sequentially isolated, fragmented, and the resulting fragment ions are measured to produce an MS/MS spectrum. This process is repeated to automatically acquire MS/MS spectra on as many different peptide ions as possible throughout the LC gradient. See Fig. 1 for a schematic showing the relationship between precursor ions in the MS scans and the resulting MS/MS scans. While the MS/MS spectrum contains the peptide fragmentation pattern, the experimental peptide mass and charge state are obtained from the precursor ion measure in the MS spectrum.To clarify terminology, the intact peptide ions in the MS scans are termed precursor ions. Fragment ions are also called product ions and MS/MS spectra are referred to as product ion spectra. MS and MS/MS spectra can also ...

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A guided tour of the Trans‐Proteomic Pipeline

Cited by 728 publications

References 48 publications

OpenMS: a flexible open-source software platform for mass spectrometry data analysis

OpenMS: a flexible open-source software platform for mass spectrometry data analysis

Identifying Proteins in Zebrafish Embryos Using Spectral Libraries Generated from Dissected Adult Organs and Tissues

A Face in the Crowd: Recognizing Peptides Through Database Search

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