Interactive Identification of Trajectories in Single-Cell RNA-seq

To build an interactive, distributed environment for analyzing single-cell RNA-seq data topology (trajectories, clusters) and associated driving genes.

This group worked to build an optimal environment to capture the full spectrum of cell types and cell states across the human body by defining a package called diffxpy, used to identify and interpret continuous trajectories and cellular lineage trees. They also built an additional python package, sfaira, to streamline the data loading process and better predict cell types.