OCRscore v1.0.0
First public release of analysis code accompanying the preprint:
Benej et al. Mitochondrial Oxygen Consumption Drives Lung Tumor Hypoxia and Resistance to Therapy via Copy Number Alteration in Mitochondrial Electron Transport Subunit NDUFB5. bioRxiv (2026).
https://doi.org/10.64898/2026.07.27.741033
What’s included
- Manuscript figure notebooks in
dissemination/manuscript/- Figure 1 — Buffa hypoxia rainclouds across cancers and lung tissues (runs from tracked data in-repo)
- Figure 3 — OCR score vs Buffa; LB/HB pathway slopes; HIF targets / MIR210 (needs local TCGA/PCAWG/
many-cancersdata) - Figure 4 — Core vs supernumerary subunit OS enrichment permutation P values (tracked Excel input)
- Supplement — multi-cancer OCR / biogenesis / mitophagy vs Buffa
- Small tracked inputs for Figure 1 under
dissemination/manuscript/data/ - Documentation for data provenance, reproducibility limits, and how to calculate the OCR score
- Branding assets (hex sticker + graphical abstract)
Calculate the OCR score
The OCR score (and Buffa hypoxia score, plus other TME signatures) is computed with:
https://github.com/spakowiczlab/tmesig
devtools::install_github("spakowiczlab/tmesig")
ocr <- tmesig::calculateMitoscore(gene_matrix, mito.genes = tmesig::inputGenes("Mitoscore"))