Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Xi, Yuanxin, Rocke, David M
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
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
_version_ 1782158480839278592
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