bioRxiv · 10.1101/2020.09.08.288662
Repeated Decision Stumping Distils Simple Rules from Single Cell Data
Abstract
Here we introduce repeated decision stumping, to distill simple models from single cell data. We develop decision trees of depth one - hence stumps - to identify in an inductive manner, gene products involved in driving cell fate transitions, and in applications to published data we are able to discover the key-players involved in these processes in an unbiased manner without prior knowledge. The approach is computationally efficient, has remarkable predictive power, and yields robust and statistically stable predictors: the same set of candidates is generated by applying the algorithm to different subsamples of the data.
Source connections
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Croydon Veleslavov, I. A., Stumpf, M. P. H.. 2020-09-09. Repeated Decision Stumping Distils Simple Rules from Single Cell Data. https://doi.org/10.1101/2020.09.08.288662
Cite the original work for its findings. Save a collection to share your selection of sources.