Functional analyses
Several functional analysis methods are available to help us better understand the changes observed in large-scale data (transcription data, chromatin accessibility data, proteomics data, metabolomics data, flow cytometry data, etc.). Most of these functional analyses can be applied to bulk or single-cell data, and can combine multiple data sources to derive comprehensive biological information.
Enrichment of metabolic or signalling pathways
We obtain functional annotations of genes from databases such as the Gene Ontology Consortium or KEGG Pathways, and apply statistical methods such as signalling pathway enrichment analysis or overrepresentation analysis to test for enrichment of metabolic pathways. This allows us to determine whether a particular experimental treatment has an impact on gene expression at the signalling pathway level.
Transcriptional regulation
Gene expression data can also be used to infer the activity of transcription factors. Using tools such as ISMARA or SCENIC and databases listing known interactions between transcription factors and target genes, we can infer transcription regulation networks and compare them between different experimental conditions, samples, or individual cells.
Intercellular communication
Finally, databases on ligand-receptor interactions and statistical methods implemented in tools such as CellChat or NicheNet allow us to detect significant intercellular communication networks. The methods described here allow us to explore a gene expression dataset from different angles, providing additional biological information beyond traditional differential gene analysis.
What we offer
- Apply and combine different functional analysis methods
- Metabolic or signalling pathway enrichment analysis
- Transcription factor activity analysis, transcriptional network analysis
- Intercellular communication analysis
What we need from you
- Raw sequencing data (provided by a sequencing centre) or gene expression count data per sample or per cell
- Details about the analysis and biological questions you wish to address with your transcriptomic dataset
- Information about the experimental conditions of the samples