A5064123115- Single-cell and spatial transcriptomics
- Bioinformatics and Genomic Networks
- Parasitic Infections and Diagnostics
- Trypanosoma species research and implications
- Parasite Biology and Host Interactions
- Gene Regulatory Network Analysis
- Parasites and Host Interactions
Wellcome Centre for Molecular Parasitology
2022-2025
University of Glasgow
2022-2025
Abstract Motivation Single-cell transcriptomics sequencing is used to compare different biological processes. However, often, those processes are asymmetric which difficult integrate. Current approaches often rely on integrating samples from each condition before either cluster-based comparisons or analysis of an inferred shared trajectory. Results We present Trajectory Alignment Gene Expression Dynamics (TrAGEDy), allows the alignment independent trajectories avoid need for error-prone...
1 Abstract Motivation Single-cell transcriptomics sequencing is used to compare different biological processes. However, often, those processes are asymmetric which difficult integrate. Current approaches often rely on integrating samples from each condition before either cluster-based comparisons or analysis of an inferred shared trajectory. Results We present Trajectory Alignment Gene Expression Dynamics (TrAGEDy), allows the alignment independent trajectories avoid need for error-prone...
Abstract The infective L3 larvae of Heligmosomoides polygyrus migrate to the small intestine where they take up residence in submucosa, triggering formation complex granulomas around parasite. Here, we employ spatial transcriptomics elucidate transcriptional intricacies and cell-cell interactions murine under both steady-state conditions response H. infection. Our findings unveil distinct signatures crypt zone, villi, granulomas, providing nuanced insights into molecular dynamics host...
Abstract Trypanosoma cruzi, the causative agent of Chagas disease, exhibits a complex life cycle with multiple hosts, stages and differentiation steps, all associated extensive transcriptomic changes. Here we present cell atlas for T. cruzi cycle, based on single transcriptomes over 31,000 cells. We validated using known stage markers population-based transcriptomics show that can be utilised to accurately annotate in novel data. The reveals many stage-associated genes key differences...