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Analyse gene expression
This tool, termed as ReactomeGSA, allows users to analyse proteomics, transcriptomics and microarray data. Its main feature is that it performs quantitative pathway analyses (so called “gene set analyses”). This increases the statistical power of the differential expression analysis, which is directly performed on the pathway level. ReactomeGSA is integrated into Reactome’s data analysis tool suite in the Analyze Data interface (Figure 18).
Input format
ReactomeGSA can analyse multiple datasets simultaneously resulting in a comparative pathway analysis. Thereby, it is possible to quickly assess whether the same effect was observed in independent experiments or studies.
ReactomeGSA currently supports quantitative proteomics, transcriptomics, and microarray data. Datasets from all of these methods can be combined in a single analysis. Thereby, ReactomeGSA can perform multi-omics pathway analyses.
The input file must be a tab-delimited text file (CSV or TSV file) where the first column contains the gene or protein identifiers and all subsequent columns the respective samples (Figure 19). The first row contains the sample names and all subsequent rows the genes / proteins.
