| Title: | Phase Error Correction and Baseline Correction for One Dimensional ('1D') 'NMR' Data |
|---|---|
| Description: | There are three distinct approaches for phase error correction, they are: a single linear model with a choice of optimization functions, multiple linear models with optimization function choices and a shrinkage-based method. The methodology is based on our new algorithms and various references (Binczyk et al. (2015) <doi:10.1186/1475-925X-14-S2-S5>,Chen et al. (2002) <doi:10.1016/S1090-7807(02)00069-1>, de Brouwer (2009) <doi:10.1016/j.jmr.2009.09.017>, Džakula (2000) <doi:10.1006/jmre.2000.2123>, Ernst (1969) <doi:10.1016/0022-2364(69)90003-1>, Liland et al. (2010) <doi:10.1366/000370210792434350>). |
| Authors: | Aixiang Jiang [aut, cre, cph]
|
| Maintainer: | Aixiang Jiang <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 1.0.5 |
| Built: | 2024-11-12 02:40:20 UTC |
| Source: | https://github.com/ajiangsfu/nmrphasing |
This dataset contains sample data for NMRphasing.
fdatfdat
A data frame with two columns, one is for NMR data in complex format, the other one is ppm
Aixiang Jiang
Multiple single linear models that minimize absolute area.
MPC_AAM(specdat, withBC = TRUE)MPC_AAM(specdat, withBC = TRUE)
specdat |
A complex number vector of observed frequency domain data. |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction |
This function is used to process phase error correction through multiple single linear models that minimize absolute area, followed by polynomial baseline correction when necessary.
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
de Brouwer, H. (2009). Evaluation of algorithms for automated phase correction of NMR spectra. J Magn Reson, 201, 230-238.
Dzakula, Z. (2000). Phase angle measurement from peak areas (PAMPAS). J Magn Reson, 146, 20-32.
Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") mpc_aam_phased1 <- MPC_AAM(fdat$frequency_domain)data("fdat") mpc_aam_phased1 <- MPC_AAM(fdat$frequency_domain)
Multiple single linear models that minimize the absolute total dispersion.
MPC_ADSM(specdat, withBC = TRUE)MPC_ADSM(specdat, withBC = TRUE)
specdat |
A complex number vector of observed frequency domain data. |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction |
This function is used to process phase error correction through multiple single linear models that minimize the absolute total dispersion, followed by polynomial baseline correction when necessary.
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
Jiang, A. (2024). Phase Error Correction in Magnetic Resonance: A Review of Models, Optimization Functions, and Optimizers in Traditional Statistics and Neural Networks. Preprints. https://doi.org/10.20944/preprints202409.2252.v1
Chen, L., Weng, Z., Goh, L., & Garland, M. (2002). An efficient algorithm for automatic phase correction of NMR spectra based on entropy minimization. Journal of Magnetic Resonance, 158, 1-2.
Ernst, R. R. (1969). Numerical Hilbert transform and automatic phase correction in magnetic resonance spectroscopy. Journal of Magnetic Resonance, 1, 7-26
Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") mpc_dsm_phased1 <- MPC_ADSM(fdat$frequency_domain)data("fdat") mpc_dsm_phased1 <- MPC_ADSM(fdat$frequency_domain)
Multiple linear models that minimize the difference between absolute area and net area.
MPC_DANM(specdat, withBC = TRUE)MPC_DANM(specdat, withBC = TRUE)
specdat |
A complex number vector of observed frequency domain data |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction. |
This function processes phase error correction through multiple linear models that minimize the difference between absolute area and net area, followed by polynomial baseline correction when necessary.
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") mpc_danm_phased1 <- MPC_DANM(fdat$frequency_domain)data("fdat") mpc_danm_phased1 <- MPC_DANM(fdat$frequency_domain)
Multiple single linear models that minimize the total dispersion.
MPC_DSM(specdat, withBC = TRUE)MPC_DSM(specdat, withBC = TRUE)
specdat |
A complex number vector of observed frequency domain data. |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction |
This function is used to process phase error correction through multiple single linear models that minimize the total dispersion, followed by polynomial baseline correction when necessary.
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
Binczyk, F., Tarnawski, R., & Polanska, J. (2015). Strategies for optimizing the phase correction algorithms in Nuclear Magnetic Resonance spectroscopy. Biomedical Engineering Online, 14 Suppl 2(Suppl 2), S5. https://doi.org/10.1186/1475-925X-14-S2-S5
Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") mpc_dsm_phased1 <- MPC_DSM(fdat$frequency_domain)data("fdat") mpc_dsm_phased1 <- MPC_DSM(fdat$frequency_domain)
Multiple single linear models based on entropy minimization with negative peak penalty.
MPC_EMP(specdat, withBC = TRUE)MPC_EMP(specdat, withBC = TRUE)
specdat |
A complex number vector of observed frequency domain data. |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction |
This function is used to process phase error correction through multiple single linear models with entropy minimization with negative peak penalty, followed by polynomial baseline correction when necessary.
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
Binczyk F, Tarnawski R, Polanska J (2015) Strategies for optimizing the phase correction algorithms in Nuclear Magnetic Resonance spectroscopy. Biomed Eng Online 14 Suppl 2:S5.
de Brouwer, H. (2009). Evaluation of algorithms for automated phase correction of NMR spectra. J Magn Reson, 201, 230-238.
Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") mpc_emp_phased1 <- MPC_EMP(fdat$frequency_domain)data("fdat") mpc_emp_phased1 <- MPC_EMP(fdat$frequency_domain)
Non-linear shrinkage
NLS(specdat, withBC = TRUE)NLS(specdat, withBC = TRUE)
specdat |
A complex number vector of observed frequency domain data. |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction |
This function is used to process phase error correction through non-linear shrinkage, followed by Polynomial baseline correction when necessary.
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") nls_phased1 <- NLS(fdat$frequency_domain)data("fdat") nls_phased1 <- NLS(fdat$frequency_domain)
Phase error correction wrap up function
NMRphasing( specDatIn, absorptionOnly = FALSE, method = c("NLS", "MPC_DANM", "MPC_EMP", "MPC_AAM", "MPC_DSM", "MPC_ADSM", "SPC_DANM", "SPC_EMP", "SPC_AAM", "SPC_DSM", "SPC_ADSM"), withBC = TRUE )NMRphasing( specDatIn, absorptionOnly = FALSE, method = c("NLS", "MPC_DANM", "MPC_EMP", "MPC_AAM", "MPC_DSM", "MPC_ADSM", "SPC_DANM", "SPC_EMP", "SPC_AAM", "SPC_DSM", "SPC_ADSM"), withBC = TRUE )
specDatIn |
Input spectrum data, which can be one of the four formats: a vector of absorption spectrum; a complex vector; a data matrix or a data frame with two columns of spectrum data, which 1st column is for absorption spectrum, and 2nd column is for dispersion spectrum |
absorptionOnly |
A logical variable to tell us if specDatIn is a a vector of absorption specrtrum, default is false |
method |
One of phase correction and baseline correction methods. There are eleven available choices, which are "NLS", "MPC_DAOM", "MPC_EMP", "MPC_AAM", "MPC_DSM", "MPC_ADSM", "SPC_DAOM", "SPC_EMP", "SPC_AAM", "SPC_DSM", "SPC_ADSM", with "NLS", non-linear shrinkage as default. |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction |
This is a wrap function to process phase error correction and baseline correction with eleven different choices.
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
Jiang, A. (2024). Phase Error Correction in Magnetic Resonance: A Review of Models, Optimization Functions, and Optimizers in Traditional Statistics and Neural Networks. Preprints. https://doi.org/10.20944/preprints202409.2252.v1
Binczyk F, Tarnawski R, Polanska J (2015) Strategies for optimizing the phase correction algorithms in Nuclear Magnetic Resonance spectroscopy. Biomed Eng Online 14 Suppl 2:S5.
Chen L, Weng Z, Goh L, Garland M (2002) An efficient algorithm for automatic phase correction of NMR spectra based on entropy minimization. J Magn Reson 158:164–168.
de Brouwer H (2009) Evaluation of algorithms for automated phase correction of NMR spectra. J Magn Reson 201:230–238.
Džakula Ž (2000) Phase Angle Measurement from Peak Areas (PAMPAS). J Magn Reson 146:20–32.
Ernst RR (1969) Numerical Hilbert transform and automatic phase correction in magnetic resonance spectroscopy. J Magn Reson 1969 1:7–26.
Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") nls_phased <- NMRphasing(specDatIn = fdat$frequency_domain, method = "NLS")data("fdat") nls_phased <- NMRphasing(specDatIn = fdat$frequency_domain, method = "NLS")
A single linear model with minimization on absolute area.
SPC_AAM(specdat, withBC = TRUE)SPC_AAM(specdat, withBC = TRUE)
specdat |
A complex number vector of observed frequency domain data |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction |
This function is to process phase error correction through a single linear model with minimization on absolute area, followed by polynomial baseline correction if necessary
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
de Brouwer, H. (2009). Evaluation of algorithms for automated phase correction of NMR spectra. J Magn Reson, 201, 230-238.
Dzakula, Z. (2000). Phase angle measurement from peak areas (PAMPAS). J Magn Reson, 146, 20-32.
Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") spc_aam_phased1 <- SPC_AAM(fdat$frequency_domain)data("fdat") spc_aam_phased1 <- SPC_AAM(fdat$frequency_domain)
A single linear model with absolute dispersion summation minimization.
SPC_ADSM(specdat, withBC = TRUE)SPC_ADSM(specdat, withBC = TRUE)
specdat |
A complex number vector of observed frequency domain data |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction |
This function is to process phase error correction through a single linear model with absolute dispersion summation minimization, followed by polynomial baseline correction if necessary
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
Jiang, A. (2024). Phase Error Correction in Magnetic Resonance: A Review of Models, Optimization Functions, and Optimizers in Traditional Statistics and Neural Networks. Preprints. https://doi.org/10.20944/preprints202409.2252.v1
Chen, L., Weng, Z., Goh, L., & Garland, M. (2002). An efficient algorithm for automatic phase correction of NMR spectra based on entropy minimization. Journal of Magnetic Resonance, 158, 1-2.
Ernst, R. R. (1969). Numerical Hilbert transform and automatic phase correction in magnetic resonance spectroscopy. Journal of Magnetic Resonance, 1, 7-26 Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") spc_dsm_phased1 <- SPC_ADSM(fdat$frequency_domain)data("fdat") spc_dsm_phased1 <- SPC_ADSM(fdat$frequency_domain)
A single linear model with Minimization of difference between absolute area and net area
SPC_DANM(specdat, withBC = TRUE)SPC_DANM(specdat, withBC = TRUE)
specdat |
A complex number vector of observed frequency domain data |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction |
This function is to process phase error correction through a single linear model with minimization of difference between absolute area and net area, followed by polynomial baseline correction if necessary
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") spc_danm_phased1 <- SPC_DANM(fdat$frequency_domain)data("fdat") spc_danm_phased1 <- SPC_DANM(fdat$frequency_domain)
A single linear model with dispersion summation minimization.
SPC_DSM(specdat, withBC = TRUE)SPC_DSM(specdat, withBC = TRUE)
specdat |
A complex number vector of observed frequency domain data |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction |
This function is to process phase error correction through a single linear model with dispersion summation minimization, followed by polynomial baseline correction if necessary
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
Binczyk, F., Tarnawski, R., & Polanska, J. (2015). Strategies for optimizing the phase correction algorithms in Nuclear Magnetic Resonance spectroscopy. Biomedical Engineering Online, 14 Suppl 2(Suppl 2), S5. https://doi.org/10.1186/1475-925X-14-S2-S5
Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") spc_dsm_phased1 <- SPC_DSM(fdat$frequency_domain)data("fdat") spc_dsm_phased1 <- SPC_DSM(fdat$frequency_domain)
A single linear model with entropy minimization with negative peak penalty
SPC_EMP(specdat, withBC = TRUE)SPC_EMP(specdat, withBC = TRUE)
specdat |
A complex number vector of observed frequency domain data |
withBC |
A logical parameter that enables/disables baseline correction after baseline correction |
This function is to process phase error correction through a single linear model with entropy minimization with negative peak penalty, followed by polynomial baseline correction if necessary
A numeric vector of phase corrected absorption spectrum
Aixiang Jiang
Binczyk F, Tarnawski R, Polanska J (2015) Strategies for optimizing the phase correction algorithms in Nuclear Magnetic Resonance spectroscopy. Biomed Eng Online 14 Suppl 2:S5.
de Brouwer, H. (2009). Evaluation of algorithms for automated phase correction of NMR spectra. J Magn Reson, 201, 230-238.
Liland KH, Almøy T, Mevik B (2010), Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra, Applied Spectroscopy 64, pp. 1007-1016.
data("fdat") mpc_emp_phased1 <- SPC_EMP(fdat$frequency_domain)data("fdat") mpc_emp_phased1 <- SPC_EMP(fdat$frequency_domain)