Abstract: A challenge in analyzing data from tumor samples is that the biopsies contain an mixture of various cells, including cancer cells, immune cells and stromal cells. This hinders the discovery of clinically relevant information and can lead to systematically biased results. A few recent analysis techniques control for such factors, but only accommodate specific types of data, or require controls which cannot be obtained from each patient. I will present our developments on statistical methods for controlling for the latent and varying fraction of tumor cells in next-generation methylation and RNA sequencing data, which aim to enable unbiased and more accurate comparison of patient-derived samples.

Speaker: Antti Häkkinen

Affiliation: Postdoctoral fellow, Genome-Scale Biology Program, Faculty of Medicine, University of Helsinki

Place of Seminar: Aalto University