Adrien Osakwe

PhD - McGill University

Supervisor

Yue Li

Research Topics

Computational Biology

Probabilistic Models

Google Scholar

GitHub

Publications

SpaTM: Topic Models for Inferring Spatially Informed Transcriptional Programs

Adrien Osakwe

Wenqi Dong

Qihuang Zhang

Robert Sladek

Yue Li

Spatial transcriptomics has revolutionized our ability to characterize tissues and diseases by contextualizing gene expression with spatial … (see more)organization. Available methods require researchers to either train a model using histology-based annotations or use annotation-free clustering approaches to uncover spatial domains. However, few methods provide researchers with a way to jointly analyze spatial data from both annotation-free and annotation-guided perspectives using consistent inductive biases and levels of interpretability. A single framework with consistent inductive biases ensures coherence and transferability across tasks, reducing the risks of conflicting assumptions. To this end, we propose the Spatial Topic Model (SpaTM), a topic-modeling framework capable of annotation-guided and annotation-free analysis of spatial transcriptomics data. SpaTM can be used to learn gene programs that represent histology-based annotations while providing researchers with the ability to infer spatial domains with an annotation-free approach if manual annotations are limited or noisy. We demonstrate SpaTM’s interpretability with its use of topic mixtures to represent cell states and transcriptional programs and how its intuitive framework facilitates the integration of annotation-guided and annotation-free analyses of spatial data with downstream analyses such as cell type deconvolution. Finally, we demonstrate how both approaches can be used to extend the analysis of large-scale snRNA-seq atlases with the inference of cell proximity and spatial annotations in human brains with Major Depressive Disorder.

2025-01-27

bioRxiv (preprint)

doi.org

GFETM: Genome Foundation-based Embedded Topic Model for scATAC-seq Modeling

Yimin Fan

Shi Han

2024-05-17

Lecture Notes in Computer Science (published)