How can I extract the gene sets with larger weights in the factors?

[nnlrl]

No description provided.

[rargelaguet]

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.

[nnlrl]

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

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------------------ 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。 - 您收到此消息是因为您创作了该帖子。 直接回复此电子邮件，在GitHub上查看，或将该线程静音。