(1) 确定 TO-GCN 的 PCC 截止值, (2) 使用初始 TF 种子生成 TO-GCN 级别的 TF 基因列表,以及 (3) 在每个 TO- GCN 级别生成一个基因列表。 地址:https://github.com/petitmingchang/TO-GCN_STAR-Protocol 注:这里的TF指转录因子。 准备基因表达数据 在进入管道之前,我们需要准备两个具有不同时间点的...
As mentioned above, there are three steps for the pipeline. Therefore, we provided a program for each step: (1) Cutoff, (2) GCN, and (3) TO-GCN. You can directly run the program by downloading the corresponding binary codes for different system platforms, Linux, MacOSX, or Windows. You...
g++ Cutoff_STAR.cpp -o Cutoff g++ TO-GCN_STAR.cpp -o TO-GCN g++ GeneLevel_STAR.cpp -o GeneLevel (1) Cutoff: Determine the PCC cutoff for TO-GCN First of all, you need postive and negative cutoff values of Pearson’s Correlation Coefficients (PCCs) for constructing the GCN. Our metho...
最后一步是确定GCN中节点的时间顺序(级别)。时间顺序由广度优先搜索(BFS)算法指定,从您选择的一组种子节点开始(在seeds.txt中列出)。在大多数情况下,我们会选择一些在第一个时间点高表达,在接下来的时间点低表达的基因作为种子。在我们的研究中,我们选择了一个ID为Zm00001d041056的基因,并运行To-GCN程序来分配C...
Github地址https://github.com/petitmingchang/TO-GCN (Fig 1) 该软件支持Mac、Windows、Linux,演示在Linux中进行。 直接git clone https://github.com/petitmingchang/TO-GCN.git 下载即可 下载后可以看到里面一共三个脚本(Fig 2):Cutoff.cpp-GCN.cpp-TO-GCN.cpp,依次运行即可。
https://www.pnas.org/content/116/8/3091#sec-1 github 用于构建时间序列共表达网络分析。适合于转录组数据挖掘。输入文件为全部的表达基因和关注的表达基因，就能得到共表达网络。
aThe C-to-G transversion efficiency induced by eOPTI-CGBE or cOPTI-CGBE of targeted Cs bearing different nucleotides 1nt upstream. N = A, T, G, or C.Pvalues above each group were calculated between the group with “GCN” group.bThe C-to-G transversion efficiency induced by eOPT...
npm itext-to-image Repository github.com/bostrom/text-to-image Homepage github.com/bostrom/text-to-image#readme Version 7.0.1 License ISC Unpacked Size 40.4 kB Total Files 19 Last publish 16 days ago Collaborators Tryon RunKit Reportmalware...
The extraction of features and construction of WSI graph representations by TIAToolbox can be easily integrated with code for training a GCN. The modular nature of TIAToolbox allows for easy integration into a Jupyter notebook as part of the toolbox examples to successfully reproduce the SlideGra...
然而,TTG任务更加强调生成一致性。具体来说,TTG任务旨在从相同的文本输入生成一致的流量情况。为了达到这种一致性,我们将GCN整合到扩散模型中,通过引入路网的空间信息来提供更强的指导。在数据集中,我们提供了一个邻域矩阵A来表示所有道路的空间关联。给定邻接矩阵A和数据xt,双层GCN可以表示为...