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Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis
BACKGROUND: We propose a statistically principled baseline correction method, derived from a parametric smoothing model. It uses a score function to describe the key features of baseline distortion and constructs an optimal baseline curve to maximize it. The parameters are determined automatically b...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2516527/ https://www.ncbi.nlm.nih.gov/pubmed/18664284 http://dx.doi.org/10.1186/1471-2105-9-324 |
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author | Xi, Yuanxin Rocke, David M |
author_facet | Xi, Yuanxin Rocke, David M |
author_sort | Xi, Yuanxin |
collection | PubMed |
description | BACKGROUND: We propose a statistically principled baseline correction method, derived from a parametric smoothing model. It uses a score function to describe the key features of baseline distortion and constructs an optimal baseline curve to maximize it. The parameters are determined automatically by using LOWESS (locally weighted scatterplot smoothing) regression to estimate the noise variance. RESULTS: We tested this method on 1D NMR spectra with different forms of baseline distortions, and demonstrated that it is effective for both regular 1D NMR spectra and metabolomics spectra with over-crowded peaks. CONCLUSION: Compared with the automatic baseline correction function in XWINNMR 3.5, the penalized smoothing method provides more accurate baseline correction for high-signal density metabolomics spectra. |
format | Text |
id | pubmed-2516527 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-25165272008-08-15 Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis Xi, Yuanxin Rocke, David M BMC Bioinformatics Methodology Article BACKGROUND: We propose a statistically principled baseline correction method, derived from a parametric smoothing model. It uses a score function to describe the key features of baseline distortion and constructs an optimal baseline curve to maximize it. The parameters are determined automatically by using LOWESS (locally weighted scatterplot smoothing) regression to estimate the noise variance. RESULTS: We tested this method on 1D NMR spectra with different forms of baseline distortions, and demonstrated that it is effective for both regular 1D NMR spectra and metabolomics spectra with over-crowded peaks. CONCLUSION: Compared with the automatic baseline correction function in XWINNMR 3.5, the penalized smoothing method provides more accurate baseline correction for high-signal density metabolomics spectra. BioMed Central 2008-07-29 /pmc/articles/PMC2516527/ /pubmed/18664284 http://dx.doi.org/10.1186/1471-2105-9-324 Text en Copyright © 2008 Xi and Rocke; 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 | Methodology Article Xi, Yuanxin Rocke, David M Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis |
title | Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis |
title_full | Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis |
title_fullStr | Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis |
title_full_unstemmed | Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis |
title_short | Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis |
title_sort | baseline correction for nmr spectroscopic metabolomics data analysis |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2516527/ https://www.ncbi.nlm.nih.gov/pubmed/18664284 http://dx.doi.org/10.1186/1471-2105-9-324 |
work_keys_str_mv | AT xiyuanxin baselinecorrectionfornmrspectroscopicmetabolomicsdataanalysis AT rockedavidm baselinecorrectionfornmrspectroscopicmetabolomicsdataanalysis |