cyberneticlibrary
← library

Analyze ENCODE functional genomics screens

functional-screen-analysisskillsetup L2★35
ammawla/encode-toolkit ↗
What it does

Analyze genome-wide CRISPR/RNAi screens for hits and pathway enrichment

Best for

Functional genomics when you have CRISPR/RNAi data and need to rank candidates by statistical rigor; MAGeCK gold standard.

Inputs
  • · screen data (gene IDs + log2 fold-change + p-value)
  • · cell type/condition
  • · background control replicates
Outputs
  • · hit gene list (FDR-corrected)
  • · pathway enrichment (KEGG/Reactome)
  • · candidate targets ranked by effect size + consistency
Requires
  • · MAGeCK (CRISPR screen statistics)
  • · clusterProfiler (enrichment)
  • · ggplot2 (visualization)
Preconditions

Screen replicate structure known (control vs treatment); gene IDs matched to reference (Ensembl/NCBI)

Failure modes
  • · replicates pooled without batch correction → inflates false positives
  • · pathway database outdated (KEGG 2015) → misses novel pathways
  • · effect size small vs noise → hits not reproducible
Trust signals
  • · MAGeCK (widely cited in CRISPR papers)
  • · FDR correction enforced
  • · Batch effect handling documented