We’re the Trynka Group at the Wellcome Sanger Institute, exploring how genetic variation shapes immune cell function and contributes to autoimmune diseases. By combining genomics, computational biology, and experimental immunology, we aim to decode how our DNA influences health and disease—and ultimately, to pave the way for better treatments.
Here you’ll find our open-source repositories, tools, and pipelines developed to advance the study of immune cell regulation, genetic association, and multi-omics integration.
We love collaboration, reproducibility, and turning complex data into biological insight—so feel free to explore, reuse, or contribute! 🧬✨
- Perez_Alcantara_pooled_iMGL
- VIDRA
- Washer_et_al_microglia_media
- Omenn_paper
- Treg_Multiomics
- T-cell-costimulation
- CellDivider
- TGlow
- tglow-r — R package for HCI feature analysis: tglow-r
- tglow-pipeline - A Nextflow pipeline for HCI processing: tglow-pipeline
- tglow-core - Python package supporting the tglow-pipeline tglow-core
- tglow-dino4cells - Adaptation of DINO4Cells which produces multi-channel embeddings tglow-dino4cells
- tglow-manuscript - Instance scripts supporting the tglow manuscript tglow-manuscript
- poodleR — Donor unmixing using least squares: poodleR
- ProliferationAnalysis — FACS proliferation analysis of complex mixtures in R: ProliferationAnalysis
- tglow-r — R package for HCI feature analysis: tglow-r
- sc-blipper — Single-cell post-processing running cNMF and gene set enrichments: sc-blipper
- tglow-pipeline - A Nextflow pipeline for HCI processing: tglow-pipeline
- CHEERS — Genetic enrichment of chromatin peaks: CHEERS
- CellDivider mlp Model training code for the CellDivider model: CellDivider_mlp