Bioinformatic Tools to Assess and Evaluate Identity at Single-Cell Resolution

To develop a tool to facilitate single-cell transcriptome quality control, and to assign and assess cell identity in an unsupervised manner.

The Morris Lab enhanced the precision of cell type classification using single-cell training data generated from the human small intestine. They developed two tools: Capybara—a tool to measure cell identity and fate transitions, and CellOracle—a python library for the analysis of Gene Regulatory Network with single-cell data. You can learn more about both Capybara and CellOracle in their associated pre-prints.