Developmental SpatioTemporal Optimal Transport
A method for aligning spatially resolved transcriptomics time-series.
There are four main functions:
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src/destot/DESTOT/align: Given a pair of ST slices from two developmental timepoints, infer a spatiotemporal alignment matrix Pi and a growth vector xi. As discussed in the paper, there are two settings we recommend for this function: the default setting for growth-rates and alignments ($\alpha = 0.2$ ,$\beta = 0.5$ ,$\gamma = 50$ ,$\epsilon = 0.1$ ), and the robust setting ($\alpha = 0.99$ ,$\beta = 0.6$ ,$\gamma = 1$ ,$\epsilon = 0.1$ ) for spatiotemporal alignments with very different geometries (e.g. with capture-frame effects). -
src/destot/DESTOT/xi_to_growth_rate: Given a growth vector xi, convert the values in the growth vector to a per-spot growth rate$J$ given the start and end timepoints. -
src/destot/metrics/growth_distortion_metric: Given a pair of ST slices, their spatiotemporal alignment matrix Pi, and the inferred growth vector xi, calculcate the growth distortion metric as in Eq. 9 of the paper. -
src.destot/metrics/migration_metric: Given a pair of ST slices and their spatiotemporal alignment matrix Pi, calculate the migration metric as in Eq. 11 of the paper.
We will soon make DeST-OT available on PyPi. In the mean time, you can download the repository and call the functions directly.
If you encounter any problem running the software, please contact Xinhao Liu at xl5434@princeton.edu or Peter Halmos at ph3641@princeton.edu
Halmos, P., Liu, X., Gold, J., Chen, F., Ding, L. & Raphael, B. J. (2024). DeST-OT: Alignment of Spatiotemporal Transcriptomics Data. bioRxiv. The journal version is under review and the citation will be updated once published.
The bioRxiv version is available here: https://www.biorxiv.org/content/10.1101/2024.03.05.583575v1, and a Zenodo registered DOI is available in the link below
