Math technique de-clutters cancer-cell data, revealing tumor evolution, treatment leads
Using increasingly cheap and rapid methods to read the billions of "letters" that comprise human genomes — including the genomes of individual cells sampled from cancerous tumors — scientists are generating far more data than they can easily interpret. Today, two scientists from Cold Spring Harbor Laboratory (CSHL) publish a mathematical method of simplifying and interpreting genome data bearing evidence of mutations, such as those that characterize specific cancers. Not only is the technique highly accurate; it has immediate utility in efforts to parse tumor cells, in order to determine a patient’s prognosis and the best approach to treatment. …