PepsNMR 1.18.0
This document provides a brief summary on how to use the PepsNMR package. In this package, pre-processing functions transform raw FID signals from 1H NMR spectroscopy into a set of interpretable spectra.
The PepsNMR package is available on Bioconductor and can be installed via BiocManager::install
:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("PepsNMR",
dependencies = c("Depends", "Imports", "Suggests"))
Note tha installing the Suggests
dependencies will install the PepsNMRData package to run the demo below.
The package needs to be loaded once installed to be used:
library(PepsNMR)
The package development version is available on Github (Master branch): https://github.com/ManonMartin/PepsNMR, although it is highly recommended to rely on the Bioconductor release version of the package to avoid any package version mismatch.
The first step is meant to access the raw data files. To import Free Induction Decays (FIDs) in Bruker format, use the ReadFids
function. This function will return a list with the FID data matrix (saved in Fid_data
) and metadata about these FIDs (saved in Fid_info
).
fidList <- ReadFids(file.path(path,dataset_name))
Fid_data <- fidList[["Fid_data"]]
Fid_info <- fidList[["Fid_info"]]
The possible directory structures are illustrated here:
Figure 1: Accepted directory structures for the raw Bruker files
And is to be linked with the possible options of the ReadFids
function:
subdirs = TRUE
, dirs.names = FALSE
subdirs = FALSE
, dirs.names = FALSE
subdirs = TRUE
, dirs.names = TRUE
subdirs = FALSE
, dirs.names = TRUE
Here is the recommended pre-processing workflow on the FIDs and the spectra once the raw data have been loaded in R:
Steps | Description |
---|---|
Group Delay Correction | Correct for the Bruker Group Delay. |
Solvent Suppression | Remove the solvent signal from the FIDs. |
Apodization | Increase the Signal-to-Noise ratio of the FIDs. |
ZeroFilling | Improve the visual representation of the spectra. |
Fourier Transform | Transform the FIDs into a spectrum and convert the frequency scale (Hz -> ppm). |
Zero Order Phase Correction | Correct for the zero order phase dephasing. |
Internal Referencing | Calibrate the spectra with an internal reference compound. Referencing with an internal (e.g. TMSP at 0 ppm) |
Baseline Correction | Remove the spectral baseline. |
Negative Values Zeroing | Set negatives values to 0. |
Warping | Warp the spectra according to a reference spectrum. |
Window Selection | Select the informative part of the spectrum. |
Bucketing | Data reduction. |
Region Removal | Set a desired spectral region to 0. |
Zone Aggregation | Aggregate a spectral region into a single peak. |
Normalization | Normalize the spectra. |
Information on each function is provided in R, (e.g. type ?ReadFids
in the R console) and methodological details are found in Martin et al. (2018).
Human serum (HS
) and urine (HU
) datasets are available as raw data (FIDs in Bruker format) and as (partially) pre-processed signals/spectra in the ad hoc PepsNMRData package that is automatically installed with PepsNMR (through ).
Here are examples of available datasets:
library(PepsNMRData)
str(FidData_HU)
#> cplx [1:24, 1:29411] 0+0i 0+0i 0+0i ...
#> - attr(*, "dimnames")=List of 2
#> ..$ : chr [1:24] "S1-D0-E1" "S1-D0-E2" "S1-D1-E2" "S2-D0-E2" ...
#> ..$ : chr [1:29411] "0" "5.1e-05" "0.000102" "0.000153" ...
str(FinalSpectra_HS)
#> cplx [1:32, 1:500] 0-371030i 0-362686i 0-216899i ...
#> - attr(*, "dimnames")=List of 2
#> ..$ : chr [1:32] "J1-D1-1D-T1" "J3-D2-1D-T8" "J3-D3-1D-T9" "J3-D4-1D-T14" ...
#> ..$ : chr [1:500] "9.98986984692192" "9.97027064485524" "9.95067144278856" "9.93107224072187" ...
Information for each dataset is available, (e.g. enter ?FidData_HS
in the R Console).
Raw Bruker FIDs can be loaded from where PepsNMRData has been intalled:
data_path <- system.file("extdata", package = "PepsNMRData")
dir(data_path)
#> [1] "Group_HS.csv" "HumanSerum"
To import FIDs in Bruker format, the ReadFids
function is used. This function will return a list with the FID data matrix (here saved as Fid_data
) and information about these FIDs (here saved as Fid_info
).
# ==== read the FIDs and their metadata =================
fidList <- ReadFids(file.path(data_path, "HumanSerum"))
Fid_data0 <- fidList[["Fid_data"]]
Fid_info <- fidList[["Fid_info"]]
kable(head(Fid_info))
TD | BYTORDA | DIGMOD | DECIM | DSPFVS | SW_h | SW | O1 | DTYPA | DT | |
---|---|---|---|---|---|---|---|---|---|---|
J1-D1-1D-T1 | 65536 | 1 | 1 | 16 | 12 | 10245.9 | 20.48638 | 2352.222 | 0 | 4.88e-05 |
J3-D2-1D-T8 | 65536 | 1 | 1 | 16 | 12 | 10245.9 | 20.48638 | 2352.222 | 0 | 4.88e-05 |
J3-D3-1D-T9 | 65536 | 1 | 1 | 16 | 12 | 10245.9 | 20.48638 | 2352.222 | 0 | 4.88e-05 |
J3-D4-1D-T14 | 65536 | 1 | 1 | 16 | 12 | 10245.9 | 20.48638 | 2352.222 | 0 | 4.88e-05 |
J4-D1-1D-T4 | 65536 | 1 | 1 | 16 | 12 | 10245.9 | 20.48638 | 2352.222 | 0 | 4.88e-05 |
J4-D2-1D-T7 | 65536 | 1 | 1 | 16 | 12 | 10245.9 | 20.48638 | 2352.222 | 0 | 4.88e-05 |
Figure 2: Raw FID
The Bruker’s digital filter originally produces a Group Delay that is removed during this step.
# ==== GroupDelayCorrection =================
Fid_data.GDC <- GroupDelayCorrection(Fid_data0, Fid_info)