2 papers
stat.AP2021
Accommodating heterogeneous missing data patterns for prostate cancer risk prediction
Matthias Neumair, Michael W. Kattan, Stephen J. Freedland +13
Objective: We compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts, in which some cohorts do not co…
q-bio.GN2017
Inferring clonal composition from multiple tumor biopsies
Matteo Manica, Hyunjae Ryan Kim, Roland Mathis +14
Explicit accounting for copy number alterations can dramatically improve mutation frequency estimates, leading to more accurate phylogeny reconstructions and subclone characterizat…