Closed nnlrl closed 5 years ago
Thank you for your reply. But I still don't understand how to extract feature information that can distinguish sample differences,similar to the first principal component.
best, wang
------------------ 原始邮件 ------------------ 发件人: "Ricard Argelaguet"notifications@github.com; 发送时间: 2019年8月8日(星期四) 晚上9:54 收件人: "bioFAM/MOFA"MOFA@noreply.github.com; 抄送: "老四"1052369741@qq.com;"Author"author@noreply.github.com; 主题: Re:[bioFAM / MOFA]如何在因子中提取具有较大权重的基因集?(#41)
您可以通过三种方式探索GSEA结果: (1)获取p值和相应的基因集统计数据并制作您自己的图表。参见runEnrichmentAnalysis (2)的输出我们提供两个可视化功能:plotEnrichment plotEnrichmentDetailed。请阅读这些功能的文档,如果不清楚,请告诉我。
此处提供了GSEA用法的示例:https://bioconductor.org/packages/release/bioc/vignettes/MOFA/inst/doc/MOFA_example_CLL.html
最好的, Ricard。
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You have two options to explore the GSEA results: (1) Fetch the p-values and the corresponding gene set statistics and do your own plots. See the output of
runEnrichmentAnalysis
(2) We provide two visualisation functions:plotEnrichment
plotEnrichmentDetailed
. Please, read the documentation of these functions and let me know if something is not clear.An example of the GSEA usage is provided here: https://bioconductor.org/packages/release/bioc/vignettes/MOFA/inst/doc/MOFA_example_CLL.html
Best, Ricard.