Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain.
Gigascience. 2017 Dec 1;6(12):1-8. doi: 10.1093/gigascience/gix111.
Networks have been proven effective representations for the analysis of biological data. As such, there exist multiple methods to extract knowledge from biological networks. However, these approaches usually limit their scope to a single biological entity type of interest or they lack the flexibility to analyze user-defined data.
We developed ProphTools, a flexible open-source command-line tool that performs prioritization on a heterogeneous network. ProphTools prioritization combines a Flow Propagation algorithm similar to a Random Walk with Restarts and a weighted propagation method. A flexible model for the representation of a heterogeneous network allows the user to define a prioritization problem involving an arbitrary number of entity types and their interconnections. Furthermore, ProphTools provides functionality to perform cross-validation tests, allowing users to select the best network configuration for a given problem. ProphTools core prioritization methodology has already been proven effective in gene-disease prioritization and drug repositioning. Here we make ProphTools available to the scientific community as flexible, open-source software and perform a new proof-of-concept case study on long noncoding RNAs (lncRNAs) to disease prioritization.
ProphTools is robust prioritization software that provides the flexibility not present in other state-of-the-art network analysis approaches, enabling researchers to perform prioritization tasks on any user-defined heterogeneous network. Furthermore, the application to lncRNA-disease prioritization shows that ProphTools can reach the performance levels of ad hoc prioritization tools without losing its generality.
网络已被证明是分析生物数据的有效表示形式。因此,存在多种从生物网络中提取知识的方法。然而,这些方法通常将其范围限制为单个感兴趣的生物实体类型,或者缺乏分析用户定义数据的灵活性。
我们开发了 ProphTools,这是一种灵活的开源命令行工具,可在异构网络上执行优先级排序。ProphTools 优先级排序结合了类似于随机游走与重启动的流传播算法和加权传播方法。异构网络的灵活表示模型允许用户定义涉及任意数量的实体类型及其相互连接的优先级排序问题。此外,ProphTools 提供了执行交叉验证测试的功能,使用户能够为给定问题选择最佳的网络配置。ProphTools 的核心优先级排序方法已在基因-疾病优先级排序和药物重定位中得到证明是有效的。在这里,我们将 ProphTools 作为灵活的开源软件提供给科学界,并对长非编码 RNA(lncRNA)疾病优先级排序进行了新的概念验证案例研究。
ProphTools 是一种稳健的优先级排序软件,它提供了其他最先进的网络分析方法所没有的灵活性,使研究人员能够在任何用户定义的异构网络上执行优先级排序任务。此外,lncRNA-疾病优先级排序的应用表明,ProphTools 可以达到特定优先级排序工具的性能水平,而不会失去其通用性。