Awesome
scTour
<img src="https://github.com/LiQian-XC/sctour/blob/main/docs/source/_static/img/scTour_head_image.png" width="400px" align="left">scTour is an innovative and comprehensive method for dissecting cellular dynamics by analysing datasets derived from single-cell genomics.
It provides a unifying framework to depict the full picture of developmental processes from multiple angles including the developmental pseudotime, vector field and latent space.
It further generalises these functionalities to a multi-task architecture for within-dataset inference and cross-dataset prediction of cellular dynamics in a batch-insensitive manner.
Key features
- cell pseudotime estimation with no need for specifying starting cells.
- transcriptomic vector field inference with no discrimination between spliced and unspliced mRNAs.
- latent space mapping by combining intrinsic transcriptomic structure with extrinsic pseudotime ordering.
- model-based prediction of pseudotime, vector field, and latent space for query cells/datasets/time intervals.
- insensitive to batch effects; robust to cell subsampling; scalable to large datasets.
Installation
pip install sctour
conda install -c conda-forge sctour
Documentation
Full documentation can be found here.