Multi-Page PapersVolume 10, Spring 2016

CFHMM: Heterogeneous Tumor CNV Classification by Hidden Markov

Aleksandar Obradovic1,

Hongjian Qi1

1 Department of Computer Science, Columbia University


We here develop and implement a Clonal Fraction Hidden Markov Model (CFHMM), to leverage positional information in classifying Tumor CNVs and their corresponding clonal fraction from log-ratio-normalized Tumor/Normal sequencing data. In simulated data, this approach shows accurate calling of CNVs for high-fraction mutations, and improvement in calling over a naïve clustering benchmark across the board, as well as useful purity estimation for dominant clones. 

Availability and Implementation: Source code and documentation is freely available at implemented in R, with all major operating systems supported.


Supplementary Information: Additional tables and figures available at