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O18Quant: A Semiautomatic Strategy for Quantitative Analysis of High-Resolution (16)O/(18)O Labeled Data
Proteolytic (18)O-labeling has been widely used in quantitative proteomics since it can uniformly label all peptides from different kinds of proteins. There have been multiple algorithms and tools developed over the last few years to analyze high-resolution proteolytic (16)O/(18)O labeled mass spect...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4037588/ https://www.ncbi.nlm.nih.gov/pubmed/24901003 http://dx.doi.org/10.1155/2014/971857 |
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author | Guo, Yan Miyagi, Masaru Zeng, Rong Sheng, Quanhu |
author_facet | Guo, Yan Miyagi, Masaru Zeng, Rong Sheng, Quanhu |
author_sort | Guo, Yan |
collection | PubMed |
description | Proteolytic (18)O-labeling has been widely used in quantitative proteomics since it can uniformly label all peptides from different kinds of proteins. There have been multiple algorithms and tools developed over the last few years to analyze high-resolution proteolytic (16)O/(18)O labeled mass spectra. We have developed a software package, O18Quant, which addresses two major issues in the previously developed algorithms. First, O18Quant uses a robust linear model (RLM) for peptide-to-protein ratio estimation. RLM can minimize the effect of outliers instead of iteratively removing them which is a common practice in other approaches. Second, the existing algorithms lack applicable implementation. We address this by implementing O18Quant using C# under Microsoft.net framework and R. O18Quant automatically calculates the peptide/protein relative ratio and provides a friendly graphical user interface (GUI) which allows the user to manually validate the quantification results at scan, peptide, and protein levels. The intuitive GUI of O18Quant can greatly enhance the user's visualization and understanding of the data analysis. O18Quant can be downloaded for free as part of the software suite ProteomicsTools. |
format | Online Article Text |
id | pubmed-4037588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-40375882014-06-04 O18Quant: A Semiautomatic Strategy for Quantitative Analysis of High-Resolution (16)O/(18)O Labeled Data Guo, Yan Miyagi, Masaru Zeng, Rong Sheng, Quanhu Biomed Res Int Research Article Proteolytic (18)O-labeling has been widely used in quantitative proteomics since it can uniformly label all peptides from different kinds of proteins. There have been multiple algorithms and tools developed over the last few years to analyze high-resolution proteolytic (16)O/(18)O labeled mass spectra. We have developed a software package, O18Quant, which addresses two major issues in the previously developed algorithms. First, O18Quant uses a robust linear model (RLM) for peptide-to-protein ratio estimation. RLM can minimize the effect of outliers instead of iteratively removing them which is a common practice in other approaches. Second, the existing algorithms lack applicable implementation. We address this by implementing O18Quant using C# under Microsoft.net framework and R. O18Quant automatically calculates the peptide/protein relative ratio and provides a friendly graphical user interface (GUI) which allows the user to manually validate the quantification results at scan, peptide, and protein levels. The intuitive GUI of O18Quant can greatly enhance the user's visualization and understanding of the data analysis. O18Quant can be downloaded for free as part of the software suite ProteomicsTools. Hindawi Publishing Corporation 2014 2014-05-11 /pmc/articles/PMC4037588/ /pubmed/24901003 http://dx.doi.org/10.1155/2014/971857 Text en Copyright © 2014 Yan Guo et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Guo, Yan Miyagi, Masaru Zeng, Rong Sheng, Quanhu O18Quant: A Semiautomatic Strategy for Quantitative Analysis of High-Resolution (16)O/(18)O Labeled Data |
title | O18Quant: A Semiautomatic Strategy for Quantitative Analysis of High-Resolution (16)O/(18)O Labeled Data |
title_full | O18Quant: A Semiautomatic Strategy for Quantitative Analysis of High-Resolution (16)O/(18)O Labeled Data |
title_fullStr | O18Quant: A Semiautomatic Strategy for Quantitative Analysis of High-Resolution (16)O/(18)O Labeled Data |
title_full_unstemmed | O18Quant: A Semiautomatic Strategy for Quantitative Analysis of High-Resolution (16)O/(18)O Labeled Data |
title_short | O18Quant: A Semiautomatic Strategy for Quantitative Analysis of High-Resolution (16)O/(18)O Labeled Data |
title_sort | o18quant: a semiautomatic strategy for quantitative analysis of high-resolution (16)o/(18)o labeled data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4037588/ https://www.ncbi.nlm.nih.gov/pubmed/24901003 http://dx.doi.org/10.1155/2014/971857 |
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