I have been using clusterProfiler, which is a very useful package for gene set analysis and visualisation. I would like to use the ‘cnetplot’ function to plot a network of GO terms and the related genes. However for larger networks, the automatic display can be confusing and it would be helpful to be able to move nodes around. In the past I could do this with with cnetplot(fixed=FALSE) option, but after updating R and re-installing clusterProfiler, the output remains static.

I am using R 3.5.3 with clusterProfiler v3.10.1 which I installed using Bioconductor 3.8. I have installed and loaded the ‘igraph’ package, and the following test code produces output in an interactive window, as desired:

library(igraph) g <- make_ring(10) tkplot(g)

Is there any way to make cnetplot output interactive, or is that functionality simply not available in the latest release?

Any help would be greatly appreciated!

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Disease ontology (DO) annotates human genes in the context of disease. DO is important annotation in translating molecular findings from high-throughput data to clinical relevance. DOSE is an R package providing semantic similarity computations among DO terms and genes which allows biologists to explore the similarities of diseases and of gene functions in disease perspective. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented to support discovering disease associations of high-throughput biological data.

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使用barplot来展示富集分析结果是很常用的,而dotplot比较barplot来说,多了一个点大小的信息,可以比barplot展示多一个信息,所以是比较推荐的,我之前已经写了《dotplot展示富集分析结果》和《dotplot for GSEA》两篇文章,dotplot虽然简单,很多人会觉得会容易用ggplot2画出来,但其实有些细节,比如《为什么画出来的点比指定的数目要多?》,有些技巧,比如《搞大你的点,让我们画真正的气泡图》,是很多新手所不具备的,图虽然简单,但老司机的飚车技能也不可小看哦,所以我在《听说你也在画dotplot,但是我不服!》的文后就说了一句话:


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Dear GuangChuangyu,

I’m trying to use the clusterProfiler package for GSE analysis on DGE data obtained from RNAseq. While I can run enrichKEGG, I’m unable to run gseKEGG basically because I don’t know how to obtain an order ranked gene list.

I work on R. I have a dataframe or matrix with gene names, log2 fold change values, pvalues and adjusted pvalues among others.

How can I get the order ranked gene list to feed in gseKEGG?

Moreover what is the more reliable way to obtain functional insight about each sample? enrichKEGG or gseKEGG?

Thank you in advance for your help.

best regards

bruno saubaméa

今天收到一封来自Université Paris Descartes的求助信,这个问题我被问过好多次了,显然很多新手都有这问题,根本不知道该怎么跑GSEA,搞不清GSEA的输入是什么。

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Author's picture

Guangchuang Yu

Bioinformatics Professor @ SMU

Bioinformatics Professor