Additional file 1 of Bioinformatics analysis of the immune cell infiltration characteristics and correlation with crucial diagnostic markers in pulmonary arterial hypertension

Additional file 1: Figure S1. PCA plots of three datasets before and after batch correction. Figure S2. The PCA plot of immune cells between PAH and control in GSE117261 dataset. Figure S3. Heatmap of 17 feature genes in GSE113439 and GSE53408 datasets. Figure S4. The ROC of 17 genes in GSE117261.  Table S1. Details of the DEGs in the dataset GSE117261. Table S2. Identification of seventeen characteristic genes of PAH using LASSO regression algorithm. Table S3. The genes in the dark olive green module by WGCNA. Table S4. The genes in the dark green module by WGCNA.

附加文件1：图S1. 批处理校正前后三个数据集的主成分分析（PCA）图。图S2. 数据集GSE117261中肺动脉高压（PAH）与对照组间免疫细胞的PCA图。图S3. 数据集GSE113439与GSE53408中17个特征基因的热图。图S4. 数据集GSE117261中17个基因的受试者工作特征（ROC）曲线。表S1. 数据集GSE117261中差异表达基因（DEGs）的详细信息。表S2. 采用最小绝对收缩和选择算子（LASSO）回归算法鉴定肺动脉高压的17个特征基因。表S3. 加权基因共表达网络分析（WGCNA）得到的深橄榄绿色模块中的基因。表S4. WGCNA得到的深绿色模块中的基因。