A systematic assessment of deep learning methods for drug response prediction: from in-vitro to clinical application

https://github.com/LihongLab/Suppl-data-Benchmark ## GDSC dataset **Table S3.** GDSC gene expression profiles for 966 cancer cell lines, where each column represents a cell line in the form of its name and tissue collection site, and each row represents a gene in the form of the HGNC symbol. **Table S4.** GDSC gene mutation profiles for 966 cancer cell lines, where each column represents a cell line in the form of its name and tissue collection site, and each row represents a gene in the form of the HGNC symbol. The wild type is coded as 1 and the wild type as 0. **Table S5.** GDSC copy number variation profiles for 966 cancer cell lines, where each column represents a cell line in the form of its name and tissue collection site, and each row represents a gene in the form of the HGNC symbol. The copy-neutral is coded as 0 and the deletion or amplification as 1. **Table S6.** GDSC drug response data for 966 cancer cell lines and 282 drugs in the form of the natural logarithm of the IC50 readout. The first column shows the cell line name and tissue collection site, the second column shows the drug name, and the third column shows the drug response readout. **Table S7.** GDSC annotations for 282 drugs include drug name, PubChem CID, PubChem canonical SMILES, Rdkit canonical SMILES, Target Pathway, standard deviation, bimodality coefficient and density coverage. ## TCGA dataset **Table S8.** TCGA gene expression profiles, where each column represents a patient in the form of TCGA patient ID, and each row represents a gene in the form of the HGNC symbol. **Table S9.** TCGA gene mutation profiles, where each column represents a patient in the form of TCGA patient ID, and each row represents a gene in the form of the HGNC symbol. The wild type is coded as 1 and the wild type as 0. **Table S10.** TCGA copy number variation profiles, where each column represents a patient in the form of TCGA patient ID, and each row represents a gene in the form of the HGNC symbol. The copy-neutral is coded as 0 and the deletion or amplification as 1. **Table S11.** TCGA clinical response data. The first column shows the TCGA patient ID, the second column shows the drug name, the third column shows the clinical response category, the fourth column shows the cancer type, and the last column shows the clinical label as responder or non-responder.### 补充数据集链接：https://github.com/LihongLab/Suppl-data-Benchmark #### GDSC数据集 **表S3**：覆盖966株癌细胞系的GDSC基因表达谱，每一列代表一株细胞系，格式为细胞系名称与组织采集位点；每一行代表一个基因，格式为HGNC基因符号（HGNC symbol）。 **表S4**：覆盖966株癌细胞系的GDSC基因突变谱，每一列代表一株细胞系，格式为细胞系名称与组织采集位点；每一行代表一个基因，格式为HGNC基因符号。其中野生型编码为1，非野生型编码为0。 **表S5**：覆盖966株癌细胞系的GDSC拷贝数变异谱，每一列代表一株细胞系，格式为细胞系名称与组织采集位点；每一行代表一个基因，格式为HGNC基因符号。其中拷贝数中性状态编码为0，基因缺失或扩增状态编码为1。 **表S6**：覆盖966株癌细胞系与282种药物的GDSC药物反应数据，以IC50值的自然对数形式呈现。第一列为细胞系名称与组织采集位点，第二列为药物名称，第三列为药物反应读数。 **表S7**：针对282种药物的GDSC注释信息，包含药物名称、PubChem CID、PubChem标准SMILES、Rdkit标准SMILES、靶点通路、标准差、双峰系数及密度覆盖率。 #### TCGA数据集 **表S8**：TCGA基因表达谱，每一列代表一名患者，格式为TCGA患者ID；每一行代表一个基因，格式为HGNC基因符号。 **表S9**：TCGA基因突变谱，每一列代表一名患者，格式为TCGA患者ID；每一行代表一个基因，格式为HGNC基因符号。其中野生型编码为1，非野生型编码为0。 **表S10**：TCGA拷贝数变异谱，每一列代表一名患者，格式为TCGA患者ID；每一行代表一个基因，格式为HGNC基因符号。其中拷贝数中性状态编码为0，基因缺失或扩增状态编码为1。 **表S11**：TCGA临床反应数据，第一列为TCGA患者ID，第二列为药物名称，第三列为临床反应类别，第四列为癌症类型，最后一列为临床标签，分为应答者与无应答者。