ggClusterNet: An R package for microbiome network analysis and modularity‐based multiple network layouts
Tao Wen,
Penghao Xie,
Shengdie Yang,
Guoqing Niu,
Xiaoyu Liu,
Zhexu Ding,
Chao Xue,
Yong‐Xin Liu,
Qirong Shen,
Jun Yuan
Affiliations
Tao Wen
Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Key Laboratory of Green Intelligent Fertilizer Innovation, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource‐Saving Fertilizers Nanjing Agricultural University Nanjing China
Penghao Xie
Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Key Laboratory of Green Intelligent Fertilizer Innovation, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource‐Saving Fertilizers Nanjing Agricultural University Nanjing China
Shengdie Yang
Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Key Laboratory of Green Intelligent Fertilizer Innovation, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource‐Saving Fertilizers Nanjing Agricultural University Nanjing China
Guoqing Niu
Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Key Laboratory of Green Intelligent Fertilizer Innovation, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource‐Saving Fertilizers Nanjing Agricultural University Nanjing China
Xiaoyu Liu
Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Key Laboratory of Green Intelligent Fertilizer Innovation, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource‐Saving Fertilizers Nanjing Agricultural University Nanjing China
Zhexu Ding
Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Key Laboratory of Green Intelligent Fertilizer Innovation, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource‐Saving Fertilizers Nanjing Agricultural University Nanjing China
Chao Xue
Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Key Laboratory of Green Intelligent Fertilizer Innovation, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource‐Saving Fertilizers Nanjing Agricultural University Nanjing China
Yong‐Xin Liu
State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design Chinese Academy of Sciences Beijing China
Qirong Shen
Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Key Laboratory of Green Intelligent Fertilizer Innovation, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource‐Saving Fertilizers Nanjing Agricultural University Nanjing China
Jun Yuan
Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Key Laboratory of Green Intelligent Fertilizer Innovation, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource‐Saving Fertilizers Nanjing Agricultural University Nanjing China
Abstract The network analysis has attracted increasing attention and interest from ecological academics, thus it is of great necessity to develop more convenient and powerful tools. For that reason, we have developed an R package, named “ggClusterNet,” to complete and display the network analysis in an easier manner. In that package, ten network layout algorithms are designed to better display the modules of microbiome network (randomClusterG, PolygonClusterG, PolygonRrClusterG, ArtifCluster, randSNEClusterG, PolygonModsquareG, PolyRdmNotdCirG, model_Gephi.2, model_igraph, and model_maptree). For the convenience of the users, many functions related to microbial network analysis, such as corMicor(), net_properties(), node_properties(), ZiPiPlot(), random_Net_compate(), are integrated to complete the network mining. Furthermore, the pipeline function named network.2() and corBionetwork() are also added for the quick achievement of the network or bipartite network analysis as well as their in‐depth mining. The ggClusterNet is publicly available via GitHub (https://github.com/taowenmicro/ggClusterNet/) or Gitee (https://gitee.com/wentaomicro/ggClusterNet) for users' access. A complete description of the usages can be found on the manuscript's GitHub page (https://github.com/taowenmicro/ggClusterNet/wiki).
