Ali Chegini

**Project description** This repository is the **computational side** of a PhD thesis (Schimmer lab, U of T Medical Biophysics): *Identifying Variable Dependencies in the Mitochondrial Proteome in AML.* The goal is to find genes that are **variably essential** — lethal in only a *subset* of AML myeloid cell lines rather than pan-essential — from DepMap CRISPR gene-effect screens, then follow the biology. **Built:** a variability engine (apps/DepMapVariablyEssential/) that scores selective essentiality across several algorithms (Static, Dynamic, the PCA/RPCA/PPCA families, Likelihood1D, plus ML classifiers), with a posterior decision-boundary framework and GO/MitoCarta3/Reactome pathway-GSEA. A core methodological point: raw variance ≠ selective essentiality — pan-essential genes swinging between "death and more death" look variable but aren't real vulnerabilities; a true hit must *cross* the essential/non-essential boundary. The pipeline was also made deterministic (exact SVD, seeded PPCA, sorted intersections). **Found:** the leading hits converge on **mitochondrial translation** — the mitoribosome and mitochondrial aminoacyl-tRNA synthetases (mt-aaRSs) — with **RARS2** as the flagship gene and YARS2/FARS2/EARS2/NARS2 as the validation panel. **Why it matters:** selective dependencies are candidate AML therapeutic targets that spare cells lacking the vulnerability; wet-lab validation follows.