BigGIM-药物反应知识图谱

数据集获取（Figshare）

• 源站标题：BigGIM-DrugResponse KG version 3.0
• DOI：10.6084/m9.figshare.28079609.v2
• 发布日期：2024-12-23
• 文件数：1 个
• 文件总体积：944.19 MB
• 源站页面：https://figshare.com/articles/dataset/BigGIM-DrugResponse_KG/28079609

命令行下载

curl -L -o "BigGIM_DrugResponse.tar" "https://ndownloader.figshare.com/files/51346649"

文件清单

• BigGIM_DrugResponse.tar（944.19 MB）

文件总体积 944.19 MB（源站 API 实测）。

数据说明

Description - BigGIM-DrugResponse KG, created and maintained by the Multiomics Provider, includes multiple knowledge graphs aggregated from public knowledge resource or derived empirical associations from omics, drug screening and functional screening datasets. It includes the concepts of diseases, drugs or chemicals, genes and proteins etc.
BigGIM-DrugResponse KG includes both empirical findings from large datasets, as well as from aggregated public knowledge resources or literature. It expands the previous BigGIM from only gene_gene_interactions to more biological concepts, such as disease, drugs, and tissue types, etc.
The categories of nodes include: Genes, Drugs (SmallMolecules), Diseases; and the categories of edges (predicates) include Gene ~ gene_associated_with_condition ~ Disease, Gene (aspect qualifier: Genetic variants) ~ associated_with_sensitivity_to ~ SmallMolecule (aspect qualifier: IC50) etc.
BigGIM II KGs includes the following components:

• BigGIM II - Drug response (mutation-based): To understand how different gene mutations are associated with different drug responses, we extracted BigGIM II- Drug response KG (mutation based). Whole Exon Sequencing data (gene mutation data) and drug screening data from GDSC study (Iorio et al., 2016, Cell 166, 740–754. PMID:27397505) were used for knowledge graph constraction. Resource data were downloaded from https://www.cancerrxgene.org/gdsc1000/GDSC1000_WebResources/Home.html. Based on the mutation status of each gene, cell lines in each tumor type were grouped into either the wild-type group or the mutated group. The significance of the difference in the drug response IC50 values between the two groups was tested using Student T-test. The effect size was measured using the following equation:n1 = len(x) # x represents a vector of IC50 values for the mutated samplesn2 = len(y) # y represents a vector of IC50 values for the wt sampless = np.sqrt(((n1 - 1)(np.std(x))(np.std(x)) + (n2 - 1) * (np.std(y)) * (np.std(y))) / (n1 + n2 -2))d = (np.mean(x) - np.mean(y)) / sreturn(d)The associations with P-value smaller than 0.05 were digested into the knowledge graph.
• BigGIM II - Drug response (gene expression ba

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.28079609.v2（source: https://figshare.com/articles/dataset/BigGIM-DrugResponse_KG/28079609）。