A frequently sought output from a shotgun proteomics experiment is a list of proteins that we believe to have been present in the analyzed sample before proteolytic digestion. The standard technique to control for err...
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A frequently sought output from a shotgun proteomics experiment is a list of proteins that we believe to have been present in the analyzed sample before proteolytic digestion. The standard technique to control for errors in such lists is to enforce a preset threshold for the false discovery rate (FDR). Many consider protein-level FDRs a difficult and vague concept, as the measurement entities, spectra, are manifestations of peptides and not proteins. Here, we argue that this confusion is unnecessary and provide a framework on how to think about protein-level FDRs, starting from its basic principle: the null hypothesis. Specifically, we point out that two competing null hypotheses are used concurrently in today's protein inference methods, which has gone unnoticed by many. Using simulations of a shotgun proteomics experiment, we show how confusing one null hypothesis for the other can lead to serious discrepancies in the FDR. Furthermore, we demonstrate how the same simulations can be used to verify FDR estimates of protein inference methods. In particular, we show that, for a simple protein inference method, decoy models can be used to accurately estimate protein-level FDRs for both competing null hypotheses.
analysis of the phosphoproteome by MS has become a key technology for the characterization of dynamic regulatory processes in the cell, since kinase and phosphatase action underlie many major biological functions. How...
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analysis of the phosphoproteome by MS has become a key technology for the characterization of dynamic regulatory processes in the cell, since kinase and phosphatase action underlie many major biological functions. However, the addition of a phosphate group to a suitable side chain often confounds informatic analysis by generating product ion spectra that are more difficult to interpret (and consequently identify) relative to unmodified peptides. Collectively, these challenges have motivated bioinformaticians to create novel software tools and pipelines to assist in the identification of phosphopeptides in proteomic mixtures, and help pinpoint or "localize" the most likely site of modification in cases where there is ambiguity. Here we review the challenges to be met and the informatics solutions available to address them for phosphoproteomic analysis, as well as highlighting the difficulties associated with using them and the implications for data standards.
data-independent acquisition (DIA) offers several advantages over data-dependent acquisition (DDA) schemes for characterizing complex protein digests analyzed by LC-MS/MS. In contrast to the sequential detection, sele...
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data-independent acquisition (DIA) offers several advantages over data-dependent acquisition (DDA) schemes for characterizing complex protein digests analyzed by LC-MS/MS. In contrast to the sequential detection, selection, and analysis of individual ions during DDA, DIA systematically parallelizes the fragmentation of all detectable ions within a wide m/z range regardless of intensity, thereby providing broader dynamic range of detected signals, improved reproducibility for identification, better sensitivity, and accuracy for quantification, and, potentially, enhanced proteome coverage. To fully exploit these advantages, composite or multiplexed fragment ion spectra generated by DIA require more elaborate processing algorithms compared to DDA. This review examines different DIA schemes and, in particular, discusses the concepts applied to and related to dataprocessing. Available software implementations for identification and quantification are presented as comprehensively as possible and examples of software usage are cited. processing workflows, including complete proprietary frameworks or combinations of modules from different open source dataprocessing packages are described and compared in terms of software availability and usability, programming language, operating system support, input/output data formats, as well as the main principles employed in the algorithms used for identification and quantification. This comparative study concludes with further discussion of current limitations and expectable improvements in the short-and midterm future.
Coronary artery disease (CAD) is currently one of the most prevalent diseases in the world population and calcium deposits in coronary arteries are one direct risk factor. These can be assessed by the calcium score (C...
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Coronary artery disease (CAD) is currently one of the most prevalent diseases in the world population and calcium deposits in coronary arteries are one direct risk factor. These can be assessed by the calcium score (CS) application, available via a computed tomography (CT) scan, which gives an accurate indication of the development of the disease. However, the ionising radiation applied to patients is high. This study aimed to optimise the protocol acquisition in order to reduce the radiation dose and explain the flow of procedures to quantify CAD. The main differences in the clinical results, when automated or semiautomated post-processing is used, will be shown, and the epidemiology, imaging, risk factors and prognosis of the disease described. The software steps and the values that allow the risk of developing CAD to be predicted will be presented. A64-row multidetector CT scan with dual source and two phantoms (pig hearts) were used to demonstrate the advantages and disadvantages of the Agatston method. The tube energy was balanced. Two measurements were obtained in each of the three experimental protocols (64, 128, 256 mAs). Considerable changes appeared between the values of CS relating to the protocol variation. The predefined standard protocol provided the lowest dose of radiation (0.43 mGy). This study found that the variation in the radiation dose between protocols, taking into consideration the dose control systems attached to the CT equipment and image quality, was not sufficient to justify changing the default protocol provided by the manufacturer.
Background: It is possible to identify thousands of phosphopeptides and -proteins in a single experiment with mass spectrometry-based phosphoproteomics. However, a current bottleneck is the downstream dataanalysis wh...
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Background: It is possible to identify thousands of phosphopeptides and -proteins in a single experiment with mass spectrometry-based phosphoproteomics. However, a current bottleneck is the downstream dataanalysis which is often laborious and requires a number of manual steps. Results: Toward automating the analysis steps, we have developed and implemented a software, PhosFox, which enables peptide-level processing of phosphoproteomic data generated by multiple protein identification search algorithms, including Mascot, Sequest, and Paragon, as well as cross-comparison of their identification results. The software supports both qualitative and quantitative phosphoproteomics studies, as well as multiple between-group comparisons. Importantly, PhosFox detects uniquely phosphorylated peptides and proteins in one sample compared to another. It also distinguishes differences in phosphorylation sites between phosphorylated proteins in different samples. Using two case study examples, a qualitative phosphoproteome dataset from human keratinocytes and a quantitative phosphoproteome dataset from rat kidney inner medulla, we demonstrate here how PhosFox facilitates an efficient and in-depth phosphoproteome dataanalysis. PhosFox was implemented in the Perl programming language and it can be run on most common operating systems. Due to its flexible interface and open source distribution, the users can easily incorporate the program into their MS dataanalysis workflows and extend the program with new features. PhosFox source code, implementation and user instructions are freely available from https://***/phintsan/phosfox. Conclusions: PhosFox facilitates efficient and more in-depth comparisons between phosphoproteins in case-control settings. The open source implementation is easily extendable to accommodate additional features for widespread application use cases.
An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the dataprocessing...
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An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing and analysis framework based on the ROOT system have been completed. Software for unfolding soft X-ray spectra has been developed to test the functions of this framework.
It is very important to monitor surrounding rock deformation in tunnel, construction. The principle, function, development and application of the system composed of a total station and computer for monitoring and anal...
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It is very important to monitor surrounding rock deformation in tunnel, construction. The principle, function, development and application of the system composed of a total station and computer for monitoring and analyzing surrounding rock deformation were discussed. The new methods of two free station of 3D measurement and its mathematic adjustment mode were presented. The development of software for total station on-board and post for computer were also described. Without centering it and measuring its height, the total station controlled by the software on-board can fulfill the whole measurements to target points. Monitoring data can be processed by the post software and results of regression analysis, forecasting information of the tunnel surrounding rock deformation can be provided in time. The practical use shows that this system is practicable, highly accurate and efficient. It satisfies the needs of safety and information construction in tunnel construction of underground engineering.
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