Department of Biosystems Science and Engineering, ETH Zürich, Swiss Institute of Bioinformatics, Basel 4058, Switzerland and.
Faculty of Statistics, Technische Universität Dortmund, Dortmund 44221, Germany.
Bioinformatics. 2016 Apr 1;32(7):968-75. doi: 10.1093/bioinformatics/btv400. Epub 2015 Jul 9.
Despite recent technological advances in genomic sciences, our understanding of cancer progression and its driving genetic alterations remains incomplete.
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.
TiMEx is available as a Bioconductor R package at www.bsse.ethz.ch/cbg/software/TiMEx
niko.beerenwinkel@bsse.ethz.ch
Supplementary data are available at Bioinformatics online.
尽管基因组科学领域最近取得了技术进步,但我们对癌症进展及其驱动的遗传改变的理解仍不完整。
我们引入了 TiMEx,这是一种用于检测遗传改变之间各种程度互斥模式的生成概率模型,这些模式可以指示癌症进展中涉及的途径。TiMEx 明确考虑了到改变的等待时间和观察时间之间的时间相互作用。在模拟研究中,我们表明我们的模型优于以前用于检测互斥性的方法。在大规模的生物数据集上,TiMEx 确定了具有强功能生物学相关性的基因组,同时还提出了新的候选基因进行生物学验证。TiMEx 相对于以前的方法具有几个优势,包括肿瘤发生的新的生成概率模型、互斥性相互作用概率的直接估计、计算效率和检测涉及低频改变的基因组的高灵敏度。
TiMEx 作为 Bioconductor R 包可在 www.bsse.ethz.ch/cbg/software/TiMEx 获得。
niko.beerenwinkel@bsse.ethz.ch
补充数据可在 Bioinformatics 在线获得。