Michael Lawrence

Michael Lawrence developed MutSig and MutSigCV, the most widely used statistical methods for identifying significantly mutated cancer driver genes from whole-exome and whole-genome sequencing data, introducing critical corrections for gene-specific mutation rate variation that dramatically reduced false-positive driver gene calls. His work at the Broad Institute has defined the statistical framework for distinguishing driver from passenger mutations in cancer genomes and has been applied across all TCGA cancer types to build the comprehensive catalogue of cancer driver genes. His methods remain the standard for cancer driver gene discovery in large-scale sequencing studies.