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This module is designed for integrative analysis of transcriptomics/proteomics and metabolomics data at pathway level.
  • Transcriptomics / Proteomics:
    • A list of significant genes (or proteins) with optional fold change values;
  • Metabolomics:
    • Targeted metabolomics: a list of significant metabolites (or compounds of interest) with optional fold change values;
    • Untargeted metabolomics: a complete peak list. Peak names must be their numeric mass (m/z) values with optional retention times;
Try our example
Example Datasets
Please select one example dataset from below:
ID TypeOrganismData DescriptionInstrumentation
Genes - Compounds
Human A multiomics study of COVID-19 (covid vs. healthy) from Ariel et al. This data includes 1,659 DE genes and 19 DE metabolites. Transcriptomics: Illumina RNA-Seq;
Metabolomics: GC-Q/E-MS.
Genes - Peaks
Human A study on clinical tolerance on infection of P. vivax between patients (Semi-immune vs. Naïve) from Li et al). Total of 625 DE genes and a complete peak list are included. Transcriptomics: Illumina HiSeq 2500;
Metabolomics: LC-HFQ/E-MS (HILIC).
Proteins - Compounds
Human A subset of a multiomics study of COVID-19. (see James R et al). This data compares server and moderate patients. 70 proteins and 186 compounds (HMDB ID) are included. Proteomics: Proximity Extension Assay;
Metabolomics: LC-Q/E-MS.
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