Department of Statistics, University of Oxford, Oxford OX1 3LB, UK.
Doctoral Training Centre, University of Oxford, Oxford OX1 3RQ, UK.
Bioinformatics. 2018 Mar 15;34(6):994-1000. doi: 10.1093/bioinformatics/btx706.
Detecting novel functional modules in molecular networks is an important step in biological research. In the absence of gold standard functional modules, functional annotations are often used to verify whether detected modules/communities have biological meaning. However, as we show, the uneven distribution of functional annotations means that such evaluation methods favor communities of well-studied proteins.
We propose a novel framework for the evaluation of communities as functional modules. Our proposed framework, CommWalker, takes communities as inputs and evaluates them in their local network environment by performing short random walks. We test CommWalker's ability to overcome annotation bias using input communities from four community detection methods on two protein interaction networks. We find that modules accepted by CommWalker are similarly co-expressed as those accepted by current methods. Crucially, CommWalker performs well not only in well-annotated regions, but also in regions otherwise obscured by poor annotation. CommWalker community prioritization both faithfully captures well-validated communities and identifies functional modules that may correspond to more novel biology.
The CommWalker algorithm is freely available at opig.stats.ox.ac.uk/resources or as a docker image on the Docker Hub at hub.docker.com/r/lueckenmd/commwalker/.
Supplementary data are available at Bioinformatics online.
在生物研究中，检测分子网络中的新功能模块是一个重要步骤。在缺乏黄金标准功能模块的情况下，功能注释通常用于验证检测到的模块/社区是否具有生物学意义。然而，正如我们所展示的，功能注释的不均匀分布意味着这种评估方法有利于研究充分的蛋白质的社区。
我们提出了一种新的框架来评估社区作为功能模块。我们提出的框架 CommWalker 将社区作为输入，通过执行短随机游走在其本地网络环境中评估它们。我们使用来自四种社区检测方法的输入社区，在两个蛋白质相互作用网络上测试 CommWalker 克服注释偏差的能力。我们发现，CommWalker 接受的模块与当前方法接受的模块具有相似的共表达性。至关重要的是，CommWalker 不仅在注释良好的区域表现良好，而且在注释较差的区域也表现良好。CommWalker 社区优先级排序不仅忠实地捕获了经过充分验证的社区，还识别出可能对应于更新颖生物学的功能模块。
CommWalker 算法可在 opig.stats.ox.ac.uk/resources 处免费获得，或在 Docker Hub 上的 docker image 处获得，地址为 hub.docker.com/r/lueckenmd/commwalker/。
补充数据可在 Bioinformatics 在线获取。
