Statistical Analysis Tools for User-Uploaded Data
A set of online tools to enable users to perform data processing, normalization, statistical analysis and functional analysis, meta-analysis on user-supplied datasets. The input format is a table of lipid annotations and sample measurements, including a row/column which groups the samples based on experimental criteria (control, disease, treated, timepoint, etc.) The objective is to enable user-friendly high-throughput analysis for both targeted and untargeted lipidomics in order to gain biological insights. Analysis options include: sample normalization, analyte scaling, plotting, univariate analysis (Volcano plots and ANOVA analysis),clustering and correlation, multivariate analysis (PCA, LDA), classification/feature analysis (Random-Forest, OPLS-DA). Metabolite names are automatically standardized to RefMet equivalents enabling metabolite class enrichment analysis approaches.
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