TiMEx: A Waiting Time Model for Mutually Exclusive Groups of Cancer Alterations

TL;DR

TiMEx is a probabilistic model that detects mutually exclusive genetic alterations in cancer, improving accuracy and sensitivity over previous methods, and identifying biologically relevant gene groups.

Contribution

Introduces TiMEx, a novel probabilistic model that explicitly accounts for temporal dynamics to detect mutual exclusivity in cancer alterations.

Findings

Outperforms previous methods in simulations

Identifies biologically relevant gene groups in large datasets

Detects low-frequency alterations with high sensitivity

Abstract

Despite recent technological advances in genomic sciences, our understanding of cancer progression and its driving genetic alterations remains incomplete. Here, we introduce TiMEx, a generative probabilistic model for detecting patterns of various degrees of mutual exclusivity across genetic alterations, which can indicate pathways involved in cancer progression. TiMEx explicitly accounts for the temporal interplay between the waiting times to alterations and the observation time. In simulation studies, we show that our model outperforms previous methods for detecting mutual exclusivity. On large-scale biological datasets, TiMEx identifies gene groups with strong functional biological relevance, while also proposing many new candidates for biological validation. TiMEx possesses several advantages over previous methods, including a novel generative probabilistic model of tumorigenesis, direct estimation of the probability of mutual exclusivity interaction, computational efficiency, as well as high sensitivity in detecting gene groups involving low-frequency alterations. R code is available at www.cbg.bsse.ethz.ch/software/TiMEx.