Microenvironment-informed inference of transcriptional progression geometry

Authors

Kobara, S., Rahman, S. A., Ribeiro, S. P., Coopersmith, C. M., Kamaleswaran, R.

Abstract

We present BIOCURRENT, a causal inference framework that reconstructs donor-specific pseudotime geometry in transcriptomic data. By modeling gene expression as a function of baseline characteristics, microenvironmental context, and latent pseudotime, BIOCURRENT enables comparison of compressed or expanded progression intervals across transcriptional state transitions. We introduce $DeltaDelta T$, a geometry-based estimator that quantifies differences in pseudotime intervals across conditions, enabling evaluation of changes in pseudotime intervals under hypothetical modulation of microenvironmental programs. Applications to thymic T-cell developmental lineages and to COVID-19 immune dysregulation reveal condition- and donor-specific distortions of progression intervals. Counterfactual simulation links microenvironmental context to changes in specific intracellular state transition intervals. By localizing deviations in pseudotime geometry, BIOCURRENT identifies whether shifts in transcriptomic programs emerge early or later along transcriptomic coordinates and reveals upstream programs associated with these distortions. Such localization supports transcriptional stage-aware mechanistic hypotheses and suggests candidate intervention checkpoints in complex biological systems.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 25 Aug 2026.

Stats

1-terrible, 9-excellent. How would you rate this preprint? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.