dna-repair

ImageJ macro for the analysis of foci (e.g. DNA damage) in nuclei/cells

SPROUT is a machine learning tool to predict the DNA repair outcome in CRISPR experiments.

SNMF: Integrated Learning of Mutational Signatures and Prediction of DNA Repair Deficiencies by Goossens S, Tepeli YI, Seale C, and Gonçalves JP (bioRxiv 2024)

DNA Gap Prediction - using scikit-learn models to classify species and resolve gaps in DNA based on species.

Code for Guix et al. 2022, Clin Cancer Res — Validation of the TGFβ/alt-EJ (βAltw) gene expression signature predicting response to genotoxic cancer therapy.

Research framework for POLE c.138del (p.Leu46Phefs*8); Confirmed germline pathogenic frameshift variant clinically consistent w/ PPAP (reported ultra-hypermutated; tumour signature confirmation pending). Mechanistic models, differential diagnosis, therapeutic strategies, and experimental priorities.

X-CRISP: Domain-Adaptable and Interpretable CRISPR Repair Outcome Prediction by Seale C and Gonçalves JP (Bioinformatics Advances 2025)

HzHeal

MUSICiAn: Genome-wide Identification of Genes Involved in DNA Repair via Control-Free Mutational Spectra Analysis by Seale CF, Barazas M, van Schendel R, Tijsterman M, and Gonçalves JP (NAR Genomics and Bioinformatics 2025)

Ancient DNA repair framework

Bioinformatic Scripts involving the generation of figures from the article "A rise in double-strand breaks sensitizes tumours to oxidative metabolism inhibitors"

Predict mechanism underlying structural variants

Code for Espín et al. 2025, NAR Cancer — hypoxia and MYC transcriptional regulation of alternative end-joining (alt-EJ) DNA repair and its prediction of cancer treatment response.

Annotates CRISPR–Cas repair outcomes from CRISPResso2 allele tables: cut geometry (blunt vs staggered), deletion orientation and size, microhomology context, and which DNA end participates in repair — with publication-ready charts and statistics.

Computes the βAltw score: a TGFβ/alternative end-joining (alt-EJ) gene expression signature score predicting outcomes and response to genotoxic cancer therapy.