Agboraw, E. | bioRxiv Science

bioRxiv2025

HBMAP: Bayesian inference of neural circuits from DNAbarcoded projection mapping

Decoding how the brain routes information through its precise, long-range wiring remains a central challenge in neuroscience. Barcode-based mapping of axonal projections allows brain-wide, high-throughput investigation of projections at single-neuron resolution offering a powerful solution. However, principled methods for statistical analysis of barcode count data that can detect common projection rules and effectively integrate datasets across subjects are lacking. To address these issues, we developed a model-based clustering approach through hierarchical Bayesian mixtures which we call hierarchical Bayesian mapping of axonal projections (HBMAP). We show that the inferred model accurately reflects the features of the data and allows simultaneous identification of projection patterns and characterization of uncertainty that accounts for subject variability. Our study presents the first Bayesian approach to barcode-based projection mapping, offering a general solution for this class of data.

neuroscience↗

bioRxiv2024

paraCell: A novel software tool for the interactive analysis and visualization of standard and dual host-parasite single cell RNA-Seq data

Advances in sequencing technology have led to a dramatic increase in the number of single-cell transcriptomic datasets available. In the field of parasitology these datasets typically describe the gene expression patterns of a given parasite species under specific experimental conditions, in specific hosts or tissues, or at different life-cycle stages. However, while this wealth of available data represents a significant resource for further research, the analysis of these datasets often requires significant computational skills, preventing a considerable proportion of the parasitology community from meaningfully incorporating existing single-cell data into their work. Here, we present paraCell, a novel software tool that automates the advanced analysis of published single-cell data without requiring any programming ability. On our free web-server, we demonstrated how to visualise data, re-analyse published Plasmodium and Trypanosoma datasets, and present novel Toxoplasma-mouse and Theileira-cow atlases to study the impact of IFN-{gamma} and host genetic susceptibility.

bioinformatics↗