Rnmr1D is the main module in the NMRProcFlow web application ( concerning the NMR spectra processing.

Installation of some dependencies

packages <- c("impute", "MassSpecWavelet","pcaMethods")
if (length(setdiff(packages, rownames(installed.packages()))) > 0) {
   BiocManager::install(setdiff(packages, rownames(installed.packages())));

packages <- c('doParallel', 'ptw', 'signal', 'speaq', 'base64enc', 'XML', 'igraph', 'ggplot2', 'plotly', 'plyr')
if (length(setdiff(packages, rownames(installed.packages()))) > 0) {
  install.packages(setdiff(packages, rownames(installed.packages())), repos='')

Installation of the R package

install_github("INRA/Rnmr1D", dependencies = TRUE)

Example of use


# Test with the provided example data
data_dir <- system.file("extra", package = "Rnmr1D")
RAWDIR <- file.path(data_dir, "CD_BBI_16P02")
CMDFILE <- file.path(data_dir, "NP_macro_cmd.txt")
SAMPLEFILE <- file.path(data_dir, "Samples.txt")

# Detect the number of Cores

# Launch the pre-processing then the processing defined in the macro-command file
out <- Rnmr1D::doProcessing(RAWDIR, cmdfile=CMDFILE, samplefile=SAMPLEFILE, ncpu=detectCores())

# Have a look on returned data structure

### Stacked Plot with a perspective effect
plotSpecMat(out$specMat, ppm_lim=c(0.5,5), K=0.33)

### Overlaid Plot
plotSpecMat(out$specMat, ppm_lim=c(0.5,5), K=0, pY=0.1)

# Get the data matrix 
outMat <- getBucketsDataset(out, norm_meth='CSN')

# Get the Signal/Noise Ratio (SNR) matrix 
outSNR <- getSnrDataset(out, c(10.2,10.5), ratio=TRUE)

# Get the bucket table
outBucket <- getBucketsTable(out)

# Get the spectra data
spectra <- getSpectraData(out)

See a more complete illustation within the vignette


You can access the vignette online :

Try the Rnmr1D package in your browser

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Rnmr1D documentation built on Nov. 10, 2021, 9:07 a.m.