DIGGIT: a Bioconductor package to infer genetic variants driving cellular phenotypes
DIGGIT: a Bioconductor package to infer genetic variants driving cellular phenotypes
复制标题
DOI：
10.1093/bioinformatics/btv499
复制
发表时间：
2015-12-15
期刊：
影响因子：
5.8
通讯作者：
Califano, Andrea
中科院分区：
文献类型：
--
作者：
Alvarez, Mariano J.;Chen, James C.;Califano, Andrea
人类疾病中驱动突变的识别通常受到队列规模和适当统计模型可用性的限制。我们提出了一种方法，系统地发现遗传变异是疾病的因果决定因素，优先考虑基因上游的功能性疾病驱动程序，从实验数据从头推断的监管网络。在这里，我们提出了一个R系统包的驱动基因推理遗传基因组信息理论的实现。
Identification of driver mutations in human diseases is often limited by cohort size and availability of appropriate statistical models. We propose a method for the systematic discovery of genetic alterations that are causal determinants of disease, by prioritizing genes upstream of functional disease drivers, within regulatory networks inferred de novo from experimental data. Here we present the implementation of Driver-gene Inference by Genetical-Genomic Information Theory as an R-system package.