Overview
We work out which factors drive expression programmes and how they are wired together.
Salient features
- Motif discovery and scanning
- Regulon and network inference
- Deep-learning binding models
Analyses we offer
Transcription analysis
Infers transcription factor activity and motif enrichment from expression or accessibility data.
Methods: pySCENIC, gimmemotifs, decoupler.
RNA-Protein interaction analysis
Predicts and analyses RNA-binding protein sites with sequence models.
Methods: RNAProt, bpnet.
DNA and protein binding studies
Learns and interprets sequence determinants of transcription factor binding.
Methods: bpnet, bpnet-lite, gimmemotifs.
Gene regulatory network inference
Reconstructs regulator-target networks and regulon activity, including from single-cell data.
Methods: scenicplus, pySCENIC.
What you receive
- A written report with methods, parameters and interpretation
- Processed data tables and publication-quality figures
- Scripts and settings so every result can be reproduced
Not sure which analysis fits your data? Contact us and we will advise.