ICPD-A New Peak Detection Algorithm for LC/MS

<p>Abstract</p> <p>Background</p> <p>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...

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Main Authors: Haskins William, Zhang Jianqiu
Format: Article
Language:English
Published: BMC 2010-12-01
Series:BMC Genomics
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spelling doaj-f6fc3bbc21e34b1fb96dde7efc3a96572020-11-25T00:42:10ZengBMCBMC Genomics1471-21642010-12-0111Suppl 3S810.1186/1471-2164-11-S3-S8ICPD-A New Peak Detection Algorithm for LC/MSHaskins WilliamZhang Jianqiu<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p>
collection DOAJ
language English
format Article
sources DOAJ
author Haskins William
Zhang Jianqiu
spellingShingle Haskins William
Zhang Jianqiu
ICPD-A New Peak Detection Algorithm for LC/MS
BMC Genomics
author_facet Haskins William
Zhang Jianqiu
author_sort Haskins William
title ICPD-A New Peak Detection Algorithm for LC/MS
title_short 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_sort icpd-a new peak detection algorithm for lc/ms
publisher BMC
series BMC Genomics
issn 1471-2164
publishDate 2010-12-01
description <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p>
work_keys_str_mv AT haskinswilliam icpdanewpeakdetectionalgorithmforlcms
AT zhangjianqiu icpdanewpeakdetectionalgorithmforlcms
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