Data normalization software tools | NMR-based metabolomics data analysis
NMR is a high-throughput analytical technique that enables simultaneous and reproducible detection of a large number of metabolites and systematic metabolic changes in biological samples. To perform an accurate quantification of the features in a metabolomic analysis, a data normalization step is generally required. Data normalization software tools cover the full range of steps from raw data processing to biomarker identification.
Provides a web-based analytical pipeline for high-throughput metabolomics studies. MetaboAnalyst aims to offer a variety of commonly used procedures for metabolomic data processing, normalization, multivariate statistical analysis, as well as data annotation. The current implementation focuses on exploratory statistical analysis, functional interpretation, and advanced statistics for translational metabolomics studies. This tool is also available as desktop version.
Facilitates improved compound identification using mass spectrometry (MS). RANSY/RAMSY is an application that reduces spectral interference and facilitates the identification of individual molecules in overlapped MS spectra. This method is designed to work using datasets that contain multiple MS spectra for the same metabolite. It can be applied for compound identification using different analytical platforms.
Permits comprehensive metabolomics data pre-processing, statistical analysis and interpretation. W4M includes computational modules for data normalization, multivariate analysis and annotation. It can create interactive web-based documents showing the results of the analyses, and users can share them with collaborators directly on the platform. This tool enables multi-omics analyses in a global systems-biology approach.
Includes widely used statistical methods to process and identify keys entities of input experiments, offers different integrative analysis methodologies and provides interactive visualization to facilitate biological interpretations. Metabox is a bioinformatics toolbox for deep phenotyping analytics that combines data processing, statistical analysis, functional analysis and integrative exploration of metabolomic data within proteomic and transcriptomic contexts. It supports in-depth analysis of metabolomic data by including four analysis modules: data normalization, statistical analysis, network construction and functional analysis.