29 citations · 30 across the 3 of their papers we have counts for
3 papers
Topical Hidden Genome: Discovering Latent Cancer Mutational Topics using a Bayesian Multilevel Context-learning Approach
Saptarshi Chakraborty, Zoe Guan, Colin B. Begg +1
Statistical inference on the cancer-site specificities of collective ultra-rare whole genome somatic mutations is an open problem. Traditional statistical methods cannot handle who…
Using the "Hidden" Genome to Improve Classification of Cancer Types
Saptarshi Chakraborty, Colin B. Begg, Ronglai Shen
It is increasingly common clinically for cancer specimens to be examined using techniques that identify somatic mutations. In principle these mutational profiles can be used to dia…
Using somatic mutation data to test tumors for clonal relatedness
Irina Ostrovnaya, Venkatraman E. Seshan, Colin B. Begg
A major challenge for cancer pathologists is to determine whether a new tumor in a patient with cancer is a metastasis or an independent occurrence of the disease. In recent years…