MOTIVATION: Despite recent technological advances in genomic sciences, our understanding of cancer progression and its driving genetic alterations remains incomplete. RESULTS: 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 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 and high sensitivity in detecting gene groups involving low-frequency alterations. AVAILABILITY AND IMPLEMENTATION: TiMEx is available as a Bioconductor R package at www.bsse.ethz.ch/cbg/software/TiMEx CONTACT: niko.beerenwinkel@bsse.ethz.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Despite recent technological advances in genomic sciences, our understanding of cancer progression and its driving genetic alterations remains incomplete. RESULTS: 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 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 and high sensitivity in detecting gene groups involving low-frequency alterations. AVAILABILITY AND IMPLEMENTATION: TiMEx is available as a Bioconductor R package at www.bsse.ethz.ch/cbg/software/TiMEx CONTACT: niko.beerenwinkel@bsse.ethz.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Sisheng Liu; Jinpeng Liu; Yanqi Xie; Tingting Zhai; Eugene W Hinderer; Arnold J Stromberg; Nathan L Vanderford; Jill M Kolesar; Hunter N B Moseley; Li Chen; Chunming Liu; Chi Wang Journal: Bioinformatics Date: 2021-06-09 Impact factor: 6.937
Authors: Francesco Iorio; Luz Garcia-Alonso; Jonathan S Brammeld; Iňigo Martincorena; David R Wille; Ultan McDermott; Julio Saez-Rodriguez Journal: Sci Rep Date: 2018-04-30 Impact factor: 4.379