depmap-crispr-essentiality

# DepMap CRISPR Gene Effect Analysis Guide ## Overview This guide covers the correct interpretation and analysis of DepMap CRISPR gene effect (Chronos) data. The most critical and common error in DepMap analyses is failing to negate the CRISPR scores when computing correlations with "essentiality." A secondary but equally damaging mistake is using bulk correlation shortcuts that mishandle per-gene NaN patterns. This guide provides the mandatory sign convention, the correct per-gene NaN-safe Spearman correlation implementation, and data loading/alignment procedures. ## Key Concepts ### DepMap CRISPR Score Convention The CRISPR gene effect score (produced by the Chronos algorithm) quantifies how gene knockout affects cell viability: - **Negative score**: gene knockout reduces cell viability -- the gene is **essential** for that cell line - **Zero score**: no measurable effect on viability - **Positive score**: gene knockout increases viability (rare, may indicate tumor-suppressive behavior) The DepMap portal distributes these scores in the file `CRISPRGeneEffect.csv`. Each row is a cell line (DepMap ID, e.g., `ACH-000001`) and each column is a gene in the format `GENE_NAME (ENTREZ_ID)`, e.g., `A1BG (1)`. ### Essentiality Sign Interpretation Because negative raw scores indicate essentiality, any analysis that asks about "essentiality" or "dependency" requires negating the raw CRISPR scores: - "Correlation with essentiality" = correlation with `-CRISPRGeneEffect` (negat...