Michael Aregger

The paper develops a method to quantify genetic interactions from CRISPR-Cas9 screens and identifies systematic variations in screen data.

The paper constructs a genome-scale genetic interaction network from 4 million double mutants in HAP1 cells, revealing conserved genetic network principles across species and uncovering novel gene functions and cancer dependencies.

The paper identifies limitations in current reproducibility metrics for CRISPR screens and advocates for context-sensitive metrics to better assess screen quality.

The paper introduces FLEX, a pipeline for benchmarking CRISPR screen data, and identifies a dominant mitochondria-associated signal in genome-wide screens.

This study maps genetic interactions in FASN-deficient cells to identify genes involved in lipid uptake and metabolic adaptation.

The paper evaluates CRISPR/Cas9 knockout screens in human cell lines and designs an optimized gRNA library to improve gene knockout efficiency and accuracy.

This study identifies and classifies human cell line essential genes using an optimized CRISPR-Cas9 screen, finding twice to thrice as many essential genes as previous RNAi studies.