decoupleR: ensemble of computational methods to infer biological activities from omics data
Heidelberg University · University Hospital Heidelberg · +2 more institutions
Abstract
Summary: Many methods allow us to extract biological activities from omics data using information from prior knowledge resources, reducing the dimensionality for increased statistical power and better interpretability. Here, we present decoupleR, a Bioconductor and Python package containing computational methods to extract these activities within a unified framework. decoupleR allows us to flexibly run any method with a given resource, including methods that leverage mode of regulation and weights of interactions, which are not present in other frameworks. Moreover, it leverages OmniPath, a meta-resource comprising over 100 databases of prior knowledge. Using decoupleR, we evaluated the performance of methods…
Citation impact
- FWCI
- 69.99
- Percentile
- 100%
- References
- 12
Authors
11- PBPau Badia-i-Mompel
Heidelberg University, University Hospital Heidelberg
- JVJesús Vélez Santiago
Heidelberg University, University Hospital Heidelberg
- JMJana M. Braunger
Heidelberg University, University Hospital Heidelberg
- CGCelina Geiß
Heidelberg University, University Hospital Heidelberg
- DDDaniel Dimitrov
Heidelberg University, University Hospital Heidelberg
Topics & keywords
- Bioconductor
- Computer science
- Python (programming language)
- Interpretability
- Leverage (statistics)
- Source code
- Data mining
- Open source