Inference and Validation of Protein Identifications

Claassen, Manfred

doi:10.1074/mcp.r111.014795

Cited by 27 publications

(22 citation statements)

References 75 publications

(54 reference statements)

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“…2b). This suggested that the higher number of false positive protein identification would be accepted if 1% peptide FDR were applied, which is consistent with published results 37 . We applied 1% protein FDR to the whole dataset to retain only high-quality protein identifications.…”

Section: Technical Validationsupporting

confidence: 91%

Generation of a murine SWATH-MS spectral library to quantify more than 11,000 proteins

Zhong

Qiu

et al. 2020

Sci Data

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targeted SWatH-MS data analysis is critically dependent on the spectral library. Comprehensive spectral libraries of human or several other organisms have been published, but the extensive spectral library for mouse, a widely used model organism is not available. Here, we present a large murine spectral library covering more than 11,000 proteins and 240,000 proteotypic peptides, which included proteins derived from 9 murine tissue samples and one murine L929 cell line. This resource supports the quantification of 67% of all murine proteins annotated by UniProtKB/Swiss-Prot. Furthermore, we applied the spectral library to SWATH-MS data from murine tissue samples. Data are available via SWATHAtlas (PASS01441).

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Section: Technical Validationsupporting

confidence: 91%

Generation of a murine SWATH-MS spectral library to quantify more than 11,000 proteins

Zhong

Qiu

et al. 2020

Sci Data

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“…The mass spectrometry discovery proteomics data (instrument raw files, centroided mzXML and identified peptides in pepXML report) used to generate the combined assay library have been deposited to the ProteomeXchange Consortium ( http://proteomecentral.proteomexchange.org ) via the PRIDE partner repository 51 with the dataset identifier PXD000953 (Data Citation 1).…”

Section: Data Recordsmentioning

confidence: 99%

“…This result is in line with observations from other large-scale datasets, where the true detectable proteins generally have many associated peptides that match redundantly to the same protein. The false positive identifications on the other hand do not show this redundancy and thus the error-rate needs to be controlled very strictly, resulting in a number of false negative identifications 51 .…”

Section: Technical Validationmentioning

confidence: 99%

A repository of assays to quantify 10,000 human proteins by SWATH-MS

et al. 2014

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Mass spectrometry is the method of choice for deep and reliable exploration of the (human) proteome. Targeted mass spectrometry reliably detects and quantifies pre-determined sets of proteins in a complex biological matrix and is used in studies that rely on the quantitatively accurate and reproducible measurement of proteins across multiple samples. It requires the one-time, a priori generation of a specific measurement assay for each targeted protein. SWATH-MS is a mass spectrometric method that combines data-independent acquisition (DIA) and targeted data analysis and vastly extends the throughput of proteins that can be targeted in a sample compared to selected reaction monitoring (SRM). Here we present a compendium of highly specific assays covering more than 10,000 human proteins and enabling their targeted analysis in SWATH-MS datasets acquired from research or clinical specimens. This resource supports the confident detection and quantification of 50.9% of all human proteins annotated by UniProtKB/Swiss-Prot and is therefore expected to find wide application in basic and clinical research. Data are available via ProteomeXchange (PXD000953-954) and SWATHAtlas (SAL00016-35).

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“…Up to date, the best validation of potential biomarkers is represented by an experimental setup carried out with different proteomic platforms. Therefore, the results of a discovery proteomics investigation can be directly validated before by directed and later by targeted proteomic platforms . A recent validation method combining antibodies recognition with MS platforms has been called SISCAPA TM (stable isotope standards and capture by anti‐peptide antibodies) .…”

Section: Validationmentioning

confidence: 99%

Unraveling the different proteomic platforms

Messana

Cabras

Iavarone

et al. 2012

J of Separation Science

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This review is addressed to scientists working outside the field of proteomics and wishes to shed a light on the possibility offered by the latest proteomics strategies. Bottom-up and top-down platforms are critically examined outlining advantages and limitations of their application to qualitative and quantitative investigations. Discovery, directed and targeted proteomics as different options for the management of the MS instrument are defined emphasizing their integration in the experimental plan to accomplish meaningful results. The issue of data validation is analyzed and discussed. The most common qualitative proteomic platforms are described, with a particular emphasis on enrichment methods to elucidate PTMs codes (i.e. ubiquitin and histone codes). Label-free and labeled methods for relative and absolute quantification are critically compared. The possible contribution of proteomics platforms to the transition from structural proteomics to functional proteomics (study of the functional connections between different proteins) and to the challenging system biology (integrated study of all the functional cellular functions) is also briefly discussed.

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Inference and Validation of Protein Identifications

Cited by 27 publications

References 75 publications

Generation of a murine SWATH-MS spectral library to quantify more than 11,000 proteins

Generation of a murine SWATH-MS spectral library to quantify more than 11,000 proteins

A repository of assays to quantify 10,000 human proteins by SWATH-MS

Unraveling the different proteomic platforms

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