cBio Center, Dana-Farber Cancer Institute and Department of Cell Biology, Harvard Medical School, Boston, MA 02215, USA.
Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA.
Nucleic Acids Res. 2021 Jan 8;49(D1):D1083-D1093. doi: 10.1093/nar/gkaa968.
CellMiner Cross-Database (CellMinerCDB, discover.nci.nih.gov/cellminercdb) allows integration and analysis of molecular and pharmacological data within and across cancer cell line datasets from the National Cancer Institute (NCI), Broad Institute, Sanger/MGH and MD Anderson Cancer Center (MDACC). We present CellMinerCDB 1.2 with updates to datasets from NCI-60, Broad Cancer Cell Line Encyclopedia and Sanger/MGH, and the addition of new datasets, including NCI-ALMANAC drug combination, MDACC Cell Line Project proteomic, NCI-SCLC DNA copy number and methylation data, and Broad methylation, genetic dependency and metabolomic datasets. CellMinerCDB (v1.2) includes several improvements over the previously published version: (i) new and updated datasets; (ii) support for pattern comparisons and multivariate analyses across data sources; (iii) updated annotations with drug mechanism of action information and biologically relevant multigene signatures; (iv) analysis speedups via caching; (v) a new dataset download feature; (vi) improved visualization of subsets of multiple tissue types; (vii) breakdown of univariate associations by tissue type; and (viii) enhanced help information. The curation and common annotations (e.g. tissues of origin and identifiers) provided here across pharmacogenomic datasets increase the utility of the individual datasets to address multiple researcher question types, including data reproducibility, biomarker discovery and multivariate analysis of drug activity.
CellMiner 跨数据库 (CellMinerCDB，discover.nci.nih.gov/cellminercdb) 允许在国家癌症研究所 (NCI)、Broad 研究所、Sanger/MGH 和 MD 安德森癌症中心 (MDACC) 的癌症细胞系数据集中整合和分析分子和药理学数据，并在这些数据集之间进行分析。我们展示了 CellMinerCDB 1.2，其中更新了来自 NCI-60、Broad 癌症细胞系百科全书和 Sanger/MGH 的数据集，并增加了新的数据集，包括 NCI-ALMANAC 药物组合、MDACC 细胞系项目蛋白质组学、NCI-SCLC DNA 拷贝数和甲基化数据以及 Broad 甲基化、遗传依赖性和代谢组学数据集。CellMinerCDB (v1.2) 与之前发布的版本相比有几个改进：(i) 新的和更新的数据集；(ii) 支持跨数据源的模式比较和多变量分析；(iii) 更新的注释，包括药物作用机制信息和生物学上相关的多基因特征；(iv) 通过缓存加速分析；(v) 新的数据集下载功能；(vi) 改进了多个组织类型的子集的可视化；(vii) 按组织类型分解单变量关联；以及 (viii) 增强了帮助信息。这里在药物基因组数据集之间提供的编目和常见注释（例如起源组织和标识符）增加了各个数据集的实用性，以解决多种研究人员的问题类型，包括数据可重复性、生物标志物发现和药物活性的多变量分析。
