Girirajan7-2019

Girirajan7-2019

Random-forest maching learning for identifying copy-number variation in the genome

A random-forest, machine-learning method for identifying copy number variation from exome-sequencing data. A forest of hundreds of decision trees is trained on a validated set of genetic deletions and duplication, the model built from these trees can then be used to accurately identify copy number variation in sample exome-sequencing data.

IMAGE: Girirajan Laboratory, Penn State