Benchmarking methods for transcription factor prioritization.
View the Project on GitHub gifford-lab/ReprogrammingRecovery
Transcription factor over-expression is a proven method for reprogramming cells to a desired cell type for regenerative medicine and therapeutic discovery. However, a general method for the identification of reprogramming factors to create an arbitrary cell type is an open problem. We examine the success rate of methods and data for directed differentiation by testing the ability of nine computational methods (CellNet, GarNet, EBSeq, AME, DREME, HOMER, KMAC, diffTF, and DeepAccess) to correctly discover and rank candidate factors for eight target cell types with known reprogramming solutions.
We generated several resources in this project that are useful to the community.
Ranking Reprogramming Factors for Directed Differentiation
Jennifer Hammelman, Tulsi Patel, Michael Closser, Hynek Wichterle, David Gifford
bioRxiv 2021.05.14.444080; doi: https://doi.org/10.1101/2021.05.14.444080