STREAM2 (Single-cell Trajectories Reconstruction, Exploration And Mapping) is an interactive pipeline capable of disentangling and visualizing complex trajectories from for single-cell omics data.
$ pip install git+https://github.com/pinellolab/STREAM2Preliminary tutorials for the usage of STREAM2 can be found at STREAM2_tutorials repository https://github.com/pinellolab/STREAM2_tutorials.
The four key innovations of STREAM2 are:
- STREAM2 can learn more biologically meaningful trajectories in a semi-supervised way by leveraging external information (e.g. time points, FACS labels, predefined relations of clusters, etc.);
- STREAM2 is able to learn not only linear or tree-like structures but also more complex graphs with loops or disconnected components;
- STREAM2 supports trajectory inference for various single-cell assays such as gene expression, chromatin accessibility, protein expression level, and DNA methylation;
- STREAM2 introduces a flexible path-based marker detection procedure. In addition, we provide a scalable and fast python package along with a comprehensive documentation website to facilitate STREAM2 analysis.
