Compare and assess different omics studies. Within BioReviews you can compare quantitative data between genomics, proteomics and metabolomics experiments.
It includes functionality for aligning genomics and proteomics results, or comparing multiple proteomics or multiple metabolomics data sets.
- Combine studies to align your big data
- Perform cluster analysis and trend analysis to find key similarities and differences in protein, metabolite or RNA quantitative data
- Determine the biological significance of your similarities and differences
- View enriched biological pathways
Another feature in this workspace is support for manual conflict resolution when a protein maps to multiple genes or a single gene maps to multiple proteins.
You can also perform multiple analyses on experiment sets, which are each shown as a tile, and view the settings used and links to the results:
- Intersection: shows overlap between every PCA-PCVG and K-means group
- K-means: shows the clusters found
- PCA-PCVG: shows the trends found
- PCA-DA PCA: considering known sample grouping
- T-test: displays a plot of log2 fold change versus the confidence or -log10(p-value), for every contrast
- Area and fold change analysis