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应用场景
PSEA (Protein Set Enrichment Analysis) with传统of富集analyze不同, 传统of富集analyzemore依赖差异protein, 这涉及到差异阈值of设定, 存in一定主观性并且只能用于显著差异ofprotein富集. 而PSEA则不局限于差异protein, 从protein集of富集角度出发, 理论上更容易囊括细微但协调性of变化对生物通路of影响, 故能兼顾差异较小ofprotein尤其is差异倍数不太大ofprotein集. 可选of富集功能for Gene Ontology功能, KEGG通路.
Analysis Method
usingGSEA软件对所haveproteininrelatively组中表达量of变化 Ratio 值进行排序, 排序之后ofprotein列表顶部can看作is上调protein, 底部is下调protein. PSEAanalyzeofis一pcs功能集下of所haveproteinin这pcs排序列表of顶部or底部富集, such as果in顶部富集, 该功能集is上调趋势; 反之, such as果in底部富集, 则is下调趋势.
图表展示
注: PSEAanalyze结果表格.其中NAMEfor通路of名字; SIZE代表该通路下ofproteinin排好序ofprotein列表中of数目; ES代表Enrichment score, 大于0 表示通路in列表of顶部富集, 小于0表示通路in列表of底部富集; NES代表归一化后ofEnrichment score; NOM p-val代表富集显著性p value; FDR q-val代表多重假设检验校正后ofp值; FWER p-val代表of也is多重假设检验校正后ofp值, 较FDR q-val更严格.
注 : PSEA显著富集通路条形图.横坐标forNES值, 纵坐标for富集到of功能或通路. 其中红色for显著富集到have序protein列表顶端of通路, 绿色for显著富集到have序protein列表底端of通路.
注: PSEA富集结果图.分成三pcs部分, 第一部分forproteinEnrichment Scoreof折线图, 横轴foraccording torelatively组中表达量变化of Ratio 值由大到小排序ofprotein, 纵轴for该通路下protein对应ofRunning ES, 折线图of峰值就is这pcs通路ofEnrichment score. 第二部分forhit, 用线条标记位于该通路下ofproteininhave序列表中of位置. 第三部分for所haveproteinofRatio值of分布图.
need撰写需求文件, 提交protein序列或protein序列号, 并提前with工程师沟通联系.
参考文献
Aravind, Subramanian, Pablo, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.[J]. Proceedings of the National Academy of Sciences of the United States of America, 2005.
