Additional file 6: of Human Alzheimer’s disease gene expression signatures and immune profile in APP mouse models: a discrete transcriptomic view of Aβ plaque pathology

Table S3. Human AD translational transcriptomic profiling. Comparative gene network analysis was carried out from the mouse models used (tgCRND8 and Tg2576 models) in our study with that of: 1) Human aging (up-regulated) 2) Human aging (down-regulated) 3) Human inflammation signature 3) ITIM/ITAM-domain associated network signature 3) Mouse microglial gene signature (Barres et al., 2013) and 4) Mouse disease-associated microglia or DAM gene signature (Keren-Sheul et al., 2017). Differentially expressed genes were identified by Pearson correlation or T-test using Matlab R2010b (Mathworks). A. p-value cutoff of < 0.001 was used to identify differentially expressed genes. The FDR corresponding to this p-value is given in each of the comparisons to convey relative signature confidence. Set annotation analysis was performed by comparing input sets to GeneGo ( www.genego.com ), Ingenuity ( www.ingenuity.com ) and KEGG ( www.genome.jp/kegg/ ) pathway sets. Bonferroni corrected hypergeometric p-values (expectation (e)-values) of less than 0.1 were considered significant overlap between sets. (XLSX 26 kb)

附表S3 人类阿尔茨海默病（Alzheimer's Disease, AD）转化转录组谱分析。本研究以所用的tgCRND8与Tg2576小鼠模型为对象开展比较基因网络分析，比对对象包括：1）人类衰老上调基因集；2）人类衰老下调基因集；3）人类炎症特征基因集；3）免疫受体酪氨酸基抑制基序（Immunoreceptor Tyrosine-based Inhibitory Motif, ITIM）/免疫受体酪氨酸基激活基序（Immunoreceptor Tyrosine-based Activatory Motif, ITAM）结构域相关网络特征基因集；3）小鼠小胶质细胞特征基因集（Barres等，2013年）；以及4）疾病相关小胶质细胞（disease-associated microglia, DAM）特征基因集（Keren-Shaul等，2017年）。差异表达基因通过Pearson相关分析或T检验进行鉴定，所用工具为Matlab R2010b（Mathworks公司）。小节A：采用p值阈值<0.001筛选差异表达基因。本次各项比较中均给出了对应该p值的错误发现率（False Discovery Rate, FDR），以体现各特征的相对置信度。基因集注释分析通过将输入基因集与GeneGo（www.genego.com）、Ingenuity（www.ingenuity.com）及京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）通路集进行比对完成。以Bonferroni校正后的超几何分布p值（期望e值）小于0.1作为基因集间存在显著重叠的判定标准。（XLSX 26 kb）