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ICPD-A New Peak Detection Algorithm for LC/MS

BACKGROUND: The identification and quantification of proteins using label-free Liquid Chromatography/Mass Spectrometry (LC/MS) play crucial roles in biological and biomedical research. Increasing evidence has shown that biomarkers are often low abundance proteins. However, LC/MS systems are subject...

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Detalles Bibliográficos
Autores principales: Zhang, Jianqiu, Haskins, William
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2999353/
https://www.ncbi.nlm.nih.gov/pubmed/21143790
http://dx.doi.org/10.1186/1471-2164-11-S3-S8
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author Zhang, Jianqiu
Haskins, William
author_facet Zhang, Jianqiu
Haskins, William
author_sort Zhang, Jianqiu
collection PubMed
description BACKGROUND: The identification and quantification of proteins using label-free Liquid Chromatography/Mass Spectrometry (LC/MS) play crucial roles in biological and biomedical research. Increasing evidence has shown that biomarkers are often low abundance proteins. However, LC/MS systems are subject to considerable noise and sample variability, whose statistical characteristics are still elusive, making computational identification of low abundance proteins extremely challenging. As a result, the inability of identifying low abundance proteins in a proteomic study is the main bottleneck in protein biomarker discovery. RESULTS: In this paper, we propose a new peak detection method called Information Combining Peak Detection (ICPD ) for high resolution LC/MS. In LC/MS, peptides elute during a certain time period and as a result, peptide isotope patterns are registered in multiple MS scans. The key feature of the new algorithm is that the observed isotope patterns registered in multiple scans are combined together for estimating the likelihood of the peptide existence. An isotope pattern matching score based on the likelihood probability is provided and utilized for peak detection. CONCLUSIONS: The performance of the new algorithm is evaluated based on protein standards with 48 known proteins. The evaluation shows better peak detection accuracy for low abundance proteins than other LC/MS peak detection methods.
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spelling pubmed-29993532010-12-09 ICPD-A New Peak Detection Algorithm for LC/MS Zhang, Jianqiu Haskins, William BMC Genomics Research BACKGROUND: The identification and quantification of proteins using label-free Liquid Chromatography/Mass Spectrometry (LC/MS) play crucial roles in biological and biomedical research. Increasing evidence has shown that biomarkers are often low abundance proteins. However, LC/MS systems are subject to considerable noise and sample variability, whose statistical characteristics are still elusive, making computational identification of low abundance proteins extremely challenging. As a result, the inability of identifying low abundance proteins in a proteomic study is the main bottleneck in protein biomarker discovery. RESULTS: In this paper, we propose a new peak detection method called Information Combining Peak Detection (ICPD ) for high resolution LC/MS. In LC/MS, peptides elute during a certain time period and as a result, peptide isotope patterns are registered in multiple MS scans. The key feature of the new algorithm is that the observed isotope patterns registered in multiple scans are combined together for estimating the likelihood of the peptide existence. An isotope pattern matching score based on the likelihood probability is provided and utilized for peak detection. CONCLUSIONS: The performance of the new algorithm is evaluated based on protein standards with 48 known proteins. The evaluation shows better peak detection accuracy for low abundance proteins than other LC/MS peak detection methods. BioMed Central 2010-12-01 /pmc/articles/PMC2999353/ /pubmed/21143790 http://dx.doi.org/10.1186/1471-2164-11-S3-S8 Text en Copyright ©2010 Zhang and Haskins; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Zhang, Jianqiu
Haskins, William
ICPD-A New Peak Detection Algorithm for LC/MS
title ICPD-A New Peak Detection Algorithm for LC/MS
title_full ICPD-A New Peak Detection Algorithm for LC/MS
title_fullStr ICPD-A New Peak Detection Algorithm for LC/MS
title_full_unstemmed ICPD-A New Peak Detection Algorithm for LC/MS
title_short ICPD-A New Peak Detection Algorithm for LC/MS
title_sort icpd-a new peak detection algorithm for lc/ms
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2999353/
https://www.ncbi.nlm.nih.gov/pubmed/21143790
http://dx.doi.org/10.1186/1471-2164-11-S3-S8
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