利用癌症免疫學收藏品擴展基因集富集分析 · Hammer Lab --- Extending Gene Set Enrichment Analysis with Cancer Immunology Collections · Hammer Lab

Gene Set Enrichment Analysis (GSEA) is a well-known and widely-used method in Computational Biology and Bioinformatics. GSEA uses a sorted list of genes (obtained by comparing gene expression levels between groups of patients) and a database of gene sets as input, and it checks whether members of a particular gene set have a non-random ordering, biasing them towards the top or the bottom of the list (i.e. enrichment). We leave the details of the method out of this blog post, but the original paper describing GSEA is a good starting point for newcomers. 基因集富集分析（GSEA）是計算生物學和生物資訊學中眾所周知且廣泛使用的方法。 GSEA 使用基因排序清單（透過比較患者組之間的基因表現量來獲得）和基因集資料庫作為輸入，並檢查特定基因集的成員是否具有非隨機排序，使它們偏向頂部或清單的底部（即豐富） 。我們在這篇文章中保留了該方法的細節，但描述 GSEA 的原始論文對於新手來說是一個很好的起點。 Gene sets often represent biologically meaningful groupings: for example, all genes that are active during controlled cell death. It is common to see these gene sets being referred as pathways and it is for this reason that GSEA is also known as pathway analysis. Thi

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• Gem Wu