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McGill University TMIC
Please choose a functional module to proceed:
Statistical Analysis
This module offers various commonly used statistical and machine learning methods including t-tests, ANOVA, PCA, PLS-DA and Orthogonal PLS-DA. It also provides clustering and visualization tools to create dendrograms and heatmaps as well as to classify based on random forests and SVM.
Enrichment Analysis
This module performs metabolite set enrichment analysis (MSEA) for human and mammalian species based on several libraries containing ~6300 groups of metabolite sets. Users can upload either 1) a list of compounds, 2) a list of compounds with concentrations, or 3) a concentration table.
Pathway Analysis
This module supports pathway analysis (integrating enrichment analysis and pathway topology analysis) and visualization for 21 model organisms, including Human, Mouse, Rat, Cow, Chicken, Zebrafish, Arabidopsis thaliana, Rice, Drosophila, Malaria, S. cerevisae, E.coli. and others, with a total of ~1600 metabolic pathways.
Time-series/Two-factor Design
This module supports temporal and two-factor data analysis including data overview, two-way ANOVA, and empirical Bayes time-series analysis for detecting distinctive temporal profiles. It also supports ANOVA-simultaneous component analysis (ASCA) to identify major patterns associated with each experimental factor.
Power Analysis
This module uses pilot data to calculate the minimum number of samples required to detect a statistically signficant difference between two populations with a given degree of confidence (called Power Analysis).
Biomarker Analysis
This module performs various ROC curve based biomarker analyses for a single or multiple biomarkers. It also allows users to manually specify biomarker models as well as new sample prediction.
Integrated Pathway Analysis
This module performs integrated metabolic pathway analysis on results obtained from combined metabolomics and gene expression studies conducted under the same experimental conditions.
Other Utilities
This module contains several common utility functions. At this moment, compound ID conversion, batch effect correction and lipidomics data analysis are available.
Choose a utility function