Evaluation of Phosphoproteomics data-driven signalling network inference

<strong>Data</strong> Each processed data set and its adjacency matrices representing gold standard networks are stored in one specific folder. The folders have the data set name. The process of obtaining the pairwise results and the evaluation metrics are divided into two main parts: <strong>1. Pairwise results</strong> First, all the data set folders have to be placed in one main folder. Then run the script: <em>RunAll_Matrices.R</em> This script: Goes through each data set folder: reads the data set calculates for each method the resulting matrix Save in the data folder one file with all resulting matrices: file type RData <strong>2. Evaluation </strong> After this first step, each data set folder has a file that contains all the resulting adjacency matrices. The second step is to run the script RunAll_Golds.R This script Goes through each folder: reads the data set reads the result adjacency matrices from RData files reads the gold networks Calculates all evaluation metrics for each result and each gold network type.<strong>数据</strong> 每个经过预处理的数据集及其代表金标准网络（gold standard networks）的邻接矩阵（adjacency matrices）均存储于以该数据集名称命名的专属文件夹中。获取成对结果与评估指标的流程分为两大主要部分： <strong>1. 成对结果生成</strong> 首先，需将所有数据集文件夹归集至同一主文件夹内，随后运行脚本<em>RunAll_Matrices.R</em>。该脚本将遍历每个数据集文件夹：读取数据集，为每种方法计算所得邻接矩阵，并将所有结果矩阵整合为一个RData格式文件保存至数据文件夹中。 <strong>2. 模型评估</strong> 完成第一步后，每个数据集文件夹中将生成一个包含所有结果邻接矩阵的文件。第二步需运行脚本<em>RunAll_Golds.R</em>，该脚本将遍历每个文件夹：读取数据集、从RData文件中加载结果邻接矩阵、读取金标准网络，并针对每种结果与每种金标准网络类型计算全部评估指标。