clusterProfiler was used to visualize DAVID results in a paper published in BMC Genomics.

Some users told me that they may want to use DAVID at some circumstances. I think it maybe a good idea to make clusterProfiler supports DAVID, so that DAVID users can use visualization functions provided by clusterProfiler.

gene = names(geneList)[abs(geneList) > 2]
david = enrichDAVID(gene = gene, idType="ENTREZ_GENE_ID", 
listType="Gene", annotation="KEGG_PATHWAY")

> summary(david)
               ID            Description GeneRatio  BgRatio       pvalue
hsa04110 hsa04110             Cell cycle     11/68 125/5085 4.254437e-06
hsa04114 hsa04114         Oocyte meiosis     10/68 110/5085 1.119764e-05
hsa03320 hsa03320 PPAR signaling pathway      7/68  69/5085 2.606715e-04
             p.adjust qvalue                                             geneID
hsa04110 0.0003998379     NA 9133/4174/890/991/1111/891/7272/8318/4085/983/9232
hsa04114 0.0005261534     NA    9133/5241/51806/3708/991/891/4085/983/9232/6790
hsa03320 0.0081354974     NA                 4312/2167/5346/5105/3158/9370/9415
hsa04110    11
hsa04114    10
hsa03320     7

There are only 5085 human genes annotated by KEGG, this is due to out-of-date DAVID data.


cnetplot(david, foldChange=geneList)

With enrichDAVID, compare DAVID functional profiles among different gene clusters is also supported.

x=compareCluster(gcSample, fun="enrichDAVID", annotation="KEGG_PATHWAY")

As I pointed out in KEGG enrichment analysis with latest online data using clusterProfiler, there are many webservers using out of date data. This may leads to different interpretation of biological results. DAVID’s data is also out of date. DAVID stopped updating database since 2010. This is why I love Bioconductor, almost all the annotation packages are maintained by Bioconductor core team and will be updated biannual. enrichGO and enrichKEGG is more reliable with more updated data than many other tools.


Yu G, Wang L, Han Y and He Q*. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS: A Journal of Integrative Biology. 2012, 16(5):284-287.