Supporting data for "Coronary artery disease biomarker discovery using computational omics approaches"

Metabolomic and lipidomic analysis in CAD using 33 mice. Plaque tissue were collected using the Multi-ABLE method and was analysed and processed using the multi-ABLE pipeline. Uploaded data includes the input data for multi-ABLE, processed data and the code to processed the data. Full data and methodology is published at https://doi.org/10.1016/j.isci.2023.106881.Proteomic analysis in CAD using 1004 samples. Plasma proteins were collected under the BioHEART study and is analysed using LC-MS. DIA-NN is used to process the LC-MS raw data. Uploaded data includes processed data and the code to generate the figures in the chapter.CITE-seq data in CAD using 51 samples. PBMC of 51 samples were collected under the BioHEART study and is analysed using CITE-seq. scClassify and Seurat is used to process and annotate the raw data. Uploaded data includes processed data and the code to generate those figures in the chapter which does not requires raw data.

本研究对冠状动脉疾病（CAD）进行了代谢组学和脂质组学分析，共涉及33只小鼠。通过Multi-ABLE方法收集斑块组织，并使用multi-ABLE流程进行数据分析和处理。上传的数据包括multi-ABLE的输入数据、处理后的数据以及数据处理的代码。完整数据和方法论已发布于https://doi.org/10.1016/j.isci.2023.106881。此外，还进行了基于1004个样本的蛋白质组学分析。在BioHEART研究中收集了血浆蛋白，并采用液相色谱-质谱联用（LC-MS）技术进行分析。DIA-NN技术被用于处理LC-MS原始数据。上传的数据包括处理后的数据和生成章节中图表的代码。针对51个样本的CITE-seq数据，在BioHEART研究中收集了51个样本的外周血单个核细胞（PBMC），并使用CITE-seq技术进行分析。scClassify和Seurat被用于处理和注释原始数据。上传的数据包括处理后的数据和生成章节中无需原始数据的图表的代码。