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Proceedings ArticleDOI

QuantWiz: A Parallel Software Package for LC-MS-based Label-Free Protein Quantification

25 Jun 2009-pp 683-687

TL;DR: This paper described the framework design and prototype development of this new domestic parallel software package called QuantWiz for high performance Liquid Chromatography (short for LC)-MS-based label-free protein quantification, and implemented the parallelization version.

AbstractNowadays Proteomics becomes more and more popular in life science. Protein quantification, especially based on mass spectrometry (short for MS) method, is perceived as an essential part of research on proteomics. There have been some algorithms and software for protein quantification based on MS. But they have difficulties on portability, applicability and longtime running. To solve these problems, we developed a new domestic parallel software package called QuantWiz for high performance Liquid Chromatography (short for LC)-MS-based label-free protein quantification. In this paper, we described the framework design and prototype development of this high performance software package firstly. Also, user interface developed for the visualization of QuantWiz is introduced. Finally, we showed implementation of the parallelization version and performance of some experiments on this software package.

Topics: Software design (55%), Software portability (54%), Software (53%)

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Citations
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Proceedings ArticleDOI
29 Nov 2010
TL;DR: This paper compared the LC-MS-based label-free protein quantification accuracy of QuantWiz with the well-known Census software package, and designed and implemented a distributed memory version parallel algorithm for Quant Wiz.
Abstract: In the context of the prosperous development of Proteomics in life science, protein quantification, especially these based on Mass Spectrometry (short for MS) method, becomes an essential part of research. In our previous work, we developed a new software package called QuantWiz for high performance Liquid Chromatography (short for LC)-MS-based label-free protein quantification. We solved those problems of portability, applicability and longtime running existed in other software for protein quantification based on MS method. In this paper, we first compared the LC-MS-based label-free protein quantification accuracy of QuantWiz with the well-known Census software package. Then we designed and implemented a distributed memory version parallel algorithm for QuantWiz. Finally, we performed scalability testing of our new parallel algorithm and showed that our new parallel algorithm can scale up to 512 processes on Dawning 5000A.

References
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Book
01 Jan 2008
Abstract: tic regression, and it concerns studying the effect of covariates on the risk of disease. The chapter includes generalized estimating equations (GEE’s) with computing using PROC GENMOD in SAS and multilevel analysis of clustered binary data using generalized linear mixed-effects models with PROC LOGISTIC. As a prelude to the following chapter on repeated-measures data, Chapter 5 presents time series analysis. The material on repeated-measures analysis uses linear additive models with GEE’s and PROC MIXED in SAS for linear mixed-effects models. Chapter 7 is about survival data analysis. All computing throughout the book is done using SAS procedures.

9,994 citations


Journal ArticleDOI
13 Mar 2003-Nature
TL;DR: The ability of mass spectrometry to identify and, increasingly, to precisely quantify thousands of proteins from complex samples can be expected to impact broadly on biology and medicine.
Abstract: Recent successes illustrate the role of mass spectrometry-based proteomics as an indispensable tool for molecular and cellular biology and for the emerging field of systems biology. These include the study of protein-protein interactions via affinity-based isolations on a small and proteome-wide scale, the mapping of numerous organelles, the concurrent description of the malaria parasite genome and proteome, and the generation of quantitative protein profiles from diverse species. The ability of mass spectrometry to identify and, increasingly, to precisely quantify thousands of proteins from complex samples can be expected to impact broadly on biology and medicine.

6,305 citations


"QuantWiz: A Parallel Software Packa..." refers background in this paper

  • ...Recently, quantification based on mass spectrometry (short for MS) turns into a core subject for many researchers [1]....

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Journal ArticleDOI
TL;DR: The 'mzXML' format is introduced, an open, generic XML (extensible markup language) representation of MS data that will facilitate data management, interpretation and dissemination in proteomics research.
Abstract: A broad range of mass spectrometers are used in mass spectrometry (MS)-based proteomics research. Each type of instrument possesses a unique design, data system and performance specifications, resulting in strengths and weaknesses for different types of experiments. Unfortunately, the native binary data formats produced by each type of mass spectrometer also differ and are usually proprietary. The diverse, nontransparent nature of the data structure complicates the integration of new instruments into preexisting infrastructure, impedes the analysis, exchange, comparison and publication of results from different experiments and laboratories, and prevents the bioinformatics community from accessing data sets required for software development. Here, we introduce the 'mzXML' format, an open, generic XML (extensible markup language) representation of MS data. We have also developed an accompanying suite of supporting programs. We expect that this format will facilitate data management, interpretation and dissemination in proteomics research.

754 citations


Journal ArticleDOI
TL;DR: The Trans‐Proteomic Pipeline is described, which makes use of open XML file formats for storage of data at the raw spectral data, peptide, and protein levels, and enables uniform analysis and exchange of MS/MS data generated from a variety of different instruments, and assigned peptides using a range of different database search programs.
Abstract: The analysis of tandem mass (MS/MS) data to identify and quantify proteins is hampered by the heterogeneity of file formats at the raw spectral data, peptide identification, and protein identification levels. Different mass spectrometers output their raw spectral data in a variety of proprietary formats, and alternative methods that assign peptides to MS/MS spectra and infer protein identifications from those peptide assignments each write their results in different formats. Here we describe an MS/MS analysis platform, the Trans-Proteomic Pipeline, which makes use of open XML file formats for storage of data at the raw spectral data, peptide, and protein levels. This platform enables uniform analysis and exchange of MS/MS data generated from a variety of different instruments, and assigned peptides using a variety of different database search programs. We demonstrate this by applying the pipeline to data sets generated by ThermoFinnigan LCQ, ABI 4700 MALDI-TOF/TOF, and Waters Q-TOF instruments, and searched in turn using SEQUEST, Mascot, and COMET.

708 citations


Journal ArticleDOI
TL;DR: The utility of the ASAPRatio program was clearly demonstrated by its speed and the accuracy of the generated protein abundance ratios and by its capability to identify specific core components of the RNA polymerase II transcription complex within a high background of copurifying proteins.
Abstract: We describe an algorithm for the automated statistical analysis of protein abundance ratios (ASAPRatio) of proteins contained in two samples. Proteins are labeled with distinct stable-isotope tags and fragmented, and the tagged peptide fragments are separated by liquid chromatography (LC) and analyzed by electrospray ionization (ESI) tandem mass spectrometry (MS/MS). The algorithm utilizes the signals recorded for the different isotopic forms of peptides of identical sequence and numerical and statistical methods, such as Savitzky-Golay smoothing filters, statistics for weighted samples, and Dixon's test for outliers, to evaluate protein abundance ratios and their associated errors. The algorithm also provides a statistical assessment to distinguish proteins of significant abundance changes from a population of proteins of unchanged abundance. To evaluate its performance, two sets of LC-ESI-MS/MS data were analyzed by the ASAPRatio algorithm without human intervention, and the data were related to the expected and manually validated values. The utility of the ASAPRatio program was clearly demonstrated by its speed and the accuracy of the generated protein abundance ratios and by its capability to identify specific core components of the RNA polymerase II transcription complex within a high background of copurifying proteins.

347 citations