学徒作业：TCGA数据库单基因gsea之COAD-READ
发表在Cancer Management and Research的简单数据挖掘杂志：Apolipoprotein C1 (APOC1) promotes tumor progression via MAPK signaling pathways in colorectal cancer，仔细下载文献学习。
数据下载
关于TCGA数据下载，我挑选了部分，写了6个数据下载系列教程：
TCGA的28篇教程- 使用R语言的cgdsr包获取TCGA数据（cBioPortal）
TCGA的28篇教程- 使用R语言的RTCGA包获取TCGA数据 （离线打包版本）
TCGA的28篇教程-使用R语言的RTCGAToolbox包获取TCGA数据（FireBrowse portal）
TCGA的28篇教程- 批量下载TCGA所有数据 （ UCSC的 XENA）
但是，建议你选择UCSC的xena数据库下载方式。
首先看表达差异
(A) APOC1 was highly expressed in CRC (n=380) samples compared to adjacent normal (n=50) samples based on The Cancer Genome Atlas (TCGA) database (unpaired t-test, P=0.012). (B) APOC1 was highly expressed in colorectal cancer samples compared to the adjacent normal samples of a matched paired group (n=25) based on The Cancer Genome Atlas (TCGA) database (paired t-test, P=0.002).
然后看生存效果
我已经在生信技能树已经多次介绍过生存分析:
而且使用TCGA数据库来看感兴趣基因的生存情况非常简单，一个网页工具即可，都无需R语言了
(F) and (G) Kaplan– Meier survival analysis according to APOC1 expression in 140 patients with CRC. The overall survival (OS) and disease-free survival (DFS) for patients with high versus low APOC1 expression. The difference is statistically significant based on the log-rank test (both P<0.001).
单基因的GSEA
首先需要根据感兴趣的基因表达量高低，对病人进行分组。
(A) GSEA-generated heatmap for highly enriched genes in the MAPK signaling pathway in the APOC1-higher expression group compared to the APOC1-lower expression group from the TCGA COAD-READ dataset.
运行GSEA，需要指定感兴趣的通路进行可视化
(B) GSEA on the TCGA COAD-READ dataset identified MAPK signaling pathways as a regulatory target of APOC1. The GSEA enrichment plot shows values for normalized enrichment score (NES) =1.87 and nominal P-value =0.004.
如果大家感兴趣GSEA分析原理和用法，看合辑
这个任务看看哪个学徒接单哦！实际上是3个分析，差异分析+生存分析+单基因GSEA