Differential pathway expression analysis in proliferating HIVneg and HIVpos GC-Tfh cells.

We used Gene Set Variation Analysis (GSVA) to determine the biological characterization, statistical significance and differences in selected databases. We performed enrichment analyses using Ingenuity Pathway Analysis (IPA) gene sets to determine the profile of GC-Tfh cell proliferation in the context of HIV or a non-HIV environment. We generated checkerboard plots representing the top lists of enriched pathways in the DEGs specific to proliferating GC-Tfh cells in the HIVneg and HIVpos contexts (Fig 4A and 4B). The top enriched pathway list in HIVneg cells is shown in the first Table sheet while the top enriched pathway list in the HIVpos cells is shown in the second Table sheet. Pathways are listed with their log2-fold change (logFC) and their nominal p-value. Statistical significance was considered with nominal p-values p (XLSX)本研究采用基因集变异分析（Gene Set Variation Analysis, GSVA）对选定数据库中的生物学特征、统计学显著性及组间差异进行解析。随后借助Ingenuity通路分析（Ingenuity Pathway Analysis, IPA）基因集开展富集分析，以明确HIV阳性（HIVpos）与HIV阴性（HIVneg）环境下生发中心滤泡辅助性T细胞（GC-Tfh）的增殖特征。我们针对HIV阴性与HIV阳性环境中特异性增殖的GC-Tfh细胞的差异表达基因（differentially expressed genes, DEGs）所富集的顶级通路列表，绘制了棋盘式图，结果如图4A与图4B所示。HIV阴性细胞的顶级富集通路列表展示于首个工作表中，HIV阳性细胞的顶级富集通路列表则展示于第二个工作表中。各通路均附带其log2倍变化（log2-fold change, logFC）及名义p值。本研究以名义p值作为统计学显著性的判定依据，相关数据存储于XLSX格式文件中。