October 4, 2017
New software uses machine learning to identify mutations in tumours without reference tissue samples
One of the main steps in analyzing cancer genomic data is to find somatic mutations, which are non-hereditary changes in DNA that may give rise to cancer. To identify these mutations, researchers will often sequence the genome of a patient’s tumour as well as the genome of their normal tissue and compare the results. But what if normal tissue samples aren’t available?
