About

Computational Trauma and Tissue Injury Research (CTIR) Link to heading

CTIR develops open-source computational tools, reproducible analysis pipelines, and teaching material at the interface of trauma, tissue-injury biology, and quantitative biomedicine. We focus on turning heterogeneous biological and clinical data — from molecular pathology and single-cell spatial measurements to clinical registries — into transparent, reusable software and workflows.

Scope Link to heading

• Method development. R packages for dimensionality reduction (songR), RNA-seq pipelines (bambamR), single-cell spatial analysis (phenoscapR), and molecular pathology data integration (molpathR).
• Reproducible research infrastructure. Templates, themes and tooling for reproducible R-based scientific websites (reflowR, hexmakR).
• Teaching. A four-course biostatistics curriculum and a tutorial library covering foundational statistics through machine learning, bioinformatics and clinical biostatistics — see Tutorials & Courses.
• Specialised parsers and tooling. Domain-specific parsers and lightweight utilities (e.g. qviewparsR for Q-View chemiluminescent ELISA data).