Peak alignment software tools | NMR-based metabolomics data analysis
Spectral alignment is one of the main processing steps in metabolomic studies involving multiple samples. When analyzing multiple spectra, the position of the peaks corresponding to the same metabolic feature may be affected by non-linear shifts. In NMR-based studies, these shifts are observed in the ppm axis and are usually introduced by differences in the chemical environment of the sample like ionic strength, pH, or protein content.
A tool for the alignment of spectral datasets. The icoshift tool for Matlab is an open source program specifically designed for solving signal alignment problems in metabonomic NMR data analysis, but it can also properly deal with other spectra-like datasets (e.g. data from other spectroscopic methods or chromatographic data). The icoshift algorithm is based on COrrelation SHIFTing of spectral Intervals and employs an FFT engine that aligns all spectra simultaneously.
Assists users nuclear magnetic resonance (NMR)-based metabonomics or metabolomics spectral processing and data analysis. Automics is a highly integrated platform that was developed to aid researchers for processing high dimensional NMR spectroscopic data. In addition, features such as data organization, data preprocessing and a wide range of data investigation techniques for multivariate data analysis, classification and regression have been implemented.
A combined chemoinformatic approach for objective and systematic analysis of untargeted 1H NMR-based metabolic profiles in quantitative genetic contexts. The R/Bioconductor mQTL.NMR package was designed to (i) perform a series of preprocessing steps restoring spectral dependency in collinear NMR data sets to reduce the multiple testing burden, (ii) carry out robust and accurate metabotype quantitative trait locus (mQTL) mapping in human cohorts as well as in rodent models, (iii) statistically enhance structural assignment of genetically determined metabolites, and (iv) illustrate results with a series of visualization tools. Built-in flexibility and implementation in the powerful R/Bioconductor framework allow key preprocessing steps such as peak alignment, normalization, or dimensionality reduction to be tailored to specific problems.
Assists users for the chemometric analysis of nuclear magnetic resonance (NMR), infrared (IR) or Raman spectroscopy data. ChemoSpec is an R package that includes modules to plot and inspect spectra, peak alignment, hierarchical cluster analysis (HCA), principal components analysis (PCA) and model-based clustering. This method was designed with metabolomics data sets in mind.
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