Isabella Boyle

The paper uses Perturb-seq to analyze gene knockouts in cancer cell lines, identifying context-specific gene dependencies and transcriptional responses.

GeneTEA uses natural language processing to analyze gene descriptions and improve overrepresentation analysis by creating a de novo gene set database that better controls false discovery.

This study benchmarks seven computational methods for correcting CN and proximity biases in CRISPR-Cas9 screens, finding AC-Chronos and CRISPRcleanR perform best in different scenarios.

The paper integrates two large CRISPR-Cas9 screens to improve the detection of gene dependencies and cancer vulnerabilities by addressing biases and batch effects.

Chronos infers gene knockout fitness effects by explicitly modelling cell proliferation dynamics after knockout, using longitudinal readouts and correcting several known screen biases.