Package: speaq 2.7.0

speaq: Tools for Nuclear Magnetic Resonance (NMR) Spectra Alignment, Peak Based Processing, Quantitative Analysis and Visualizations

Makes Nuclear Magnetic Resonance spectroscopy (NMR spectroscopy) data analysis as easy as possible by only requiring a small set of functions to perform an entire analysis. 'speaq' offers the possibility of raw spectra alignment and quantitation but also an analysis based on features whereby the spectra are converted to peaks which are then grouped and turned into features. These features can be processed with any number of statistical tools either included in 'speaq' or available elsewhere on CRAN. More details can be found in Vu et al. (2011) <doi:10.1186/1471-2105-12-405> and Beirnaert et al. (2018) <doi:10.1371/journal.pcbi.1006018>.

Authors:Charlie Beirnaert, Trung Nghia Vu, Pieter Meysman, Kris Laukens and Dirk Valkenborg

speaq_2.7.0.tar.gz
speaq_2.7.0.zip(r-4.7)speaq_2.7.0.zip(r-4.6)speaq_2.7.0.zip(r-4.5)
speaq_2.7.0.tgz(r-4.6-any)speaq_2.7.0.tgz(r-4.5-any)
speaq_2.7.0.tar.gz(r-4.7-any)speaq_2.7.0.tar.gz(r-4.6-any)
speaq_2.7.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
speaq/json (API)

# Install 'speaq' in R:
install.packages('speaq', repos = c('https://beirnaert.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/beirnaert/speaq/issues

Datasets:

On CRAN:

Conda:

7.15 score 9 stars 3 packages 35 scripts 580 downloads 5 mentions 29 exports 63 dependencies

Last updated from:3fa92499b7. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE213
source / vignettesOK364
linux-release-x86_64NOTE221
macos-release-arm64NOTE209
macos-oldrel-arm64NOTE154
windows-develNOTE143
windows-releaseNOTE153
windows-oldrelNOTE152
wasm-releaseOK157

Exports:AddPlottingStuffBuildFeatureMatrixBuildRawDataMatrixBWRcreateNullSamplingdetectSpecPeaksdohClusterdohClusterCustommedSegmentsdoShiftdrawBWdrawSpecdrawSpecPPMfindReffindSegPeakListfindShiftStepFFTgetWaveletPeaksGetWinedata.subsethclust.groupinghClustAlignHMDBsearchRmakeSimulatedDataPeakFillingPeakGrouperregroupRrelevant.features.preturnLocalMaximaROIplotSCANTSilhouetR

Dependencies:askpasscliclustercodetoolscpp11curldata.tabledigestdoRNGdoSNOWfarverforeachggplot2gluegridExtragtablehttrimputeisobanditeratorsitertoolsjsonlitelabelinglatticelifecyclemagrittrMassSpecWaveletMatrixmimemissForestopensslpillarpkgconfigplyrR6randomForestrangerrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRdpackreshape2RfastrlangrngtoolsrvestS7scalesselectrsnowstringistringrsystibbleutf8vctrsviridisLitewithrxml2zigg

speaq 2.0 function illustrations
speaq 2.0 | Plotting the raw wine data | From spectra via peaks to peak groups (features) | Plotting the peak data | Intermezzo: PCA | removing the rose wine | A differential analysis based on linear models
Rendered fromspeaq2_illustrations.Rmdusingknitr::rmarkdown

Last update: 2019-02-22
Started: 2017-05-09

User guide for speaq package version <= 1.2.3
Preface | Introduction | Data input | Landmark peak detection | Reference finding | Spectral alignment | Automatically detect the optimal maxShift | Spectral alignment with selected segments | Spectral plots | Quantitative analysis | References
Rendered fromclassic_speaq_vignette.Rmdusingknitr::rmarkdown

Last update: 2018-11-20
Started: 2017-05-11

Readme and manuals

Help Manual

Help pageTopics
Add plotting variablesAddPlottingStuff
Build a Feature matrix from the with speaq 2.0 processed dataBuildFeatureMatrix
Build a raw data matrix (spectra) from spectra of unequal lengthBuildRawDataMatrix
BW ratio calculationBWR
Building a null hypothesis datacreateNullSampling
Peak detection for spectradetectSpecPeaks
CluPA function for multiple spectra.dohCluster
Use CluPA for alignment with additional informationdohClusterCustommedSegments
Segment shiftdoShift
BW and percentile ratios plotdrawBW
Spectral plotdrawSpec
Plot NMR spectra from a spectra data matrixdrawSpecPPM
Reference findingfindRef
Selecting the peaks in a segmentfindSegPeakList
Finding the shift-step by using Fast Fourier Transform cross- correlationfindShiftStepFFT
Convert raw NMR spectra to peak data by using waveletsgetWaveletPeaks
Get subset of Winedata for code examplesGetWinedata.subset
Grouping with hierarchical clustering (used in the PeakGrouper function)hclust.grouping
CluPA function for two spectra.hClustAlign
Submit 1H NMR peaks to HMDB for compound searchHMDBsearchR
Create a simulated NMR spectral datamakeSimulatedData
Peak filling of any missed peaksPeakFilling
Peak grouping with hierarchical clusteringPeakGrouper
Regroup faulty grouped peaksregroupR
Identify features (columns in the datamatrix) which are significantly associated with the outcome.relevant.features.p
Local maximum detectionreturnLocalMaxima
Plot NMR spectra, together with raw and grouped peaksROIplot
SCAle, Normalize and Transform a data matrixSCANT
SilhouetRSilhouetR
Wine datasetWinedata