Hi,
I am using ClusterProfiler to compare GO therm enrichment between genes clusters. With enrichGO() or compareCluster(), if I put a pvalue threeshold of 1, nothing is reported for a specific GO term and a specific cluster (no corresponding line in the summary of the result), this mean that there were no overlap at all between the cluster and the GO-term gene set?
Hi,
> CompareGO <- compareCluster(ClusterList, pvalueCutoff=1,readable=T, organism="mouse", pAdjustMethod="none", fun="enrichGO",ont="BP" )
> Sum<-summary(CompareGO)
> Sum[Sum$ID=="GO:0010498",1:4]
Cluster ID Description GeneRatio
544 1 GO:0010498 proteasomal protein catabolic process 7/372
5223 7 GO:0010498 proteasomal protein catabolic process 9/376
7136 9 GO:0010498 proteasomal protein catabolic process 7/668
In this example, there is no genes annotated by GO:0010498 in clusters 2:6 and 8.
Please also bare in mind, enrichGO contains a parameter minGSSize with default value of 5, so there maybe some clusters have genes annotated by GO:0010498 but the gene number is lower than 5 and was omitted. Of course, you can set minGSSize = 1.
Bests,
Guangchuang
Can you post an example?
Hi Guangchuang Yu,
Here is an example:
> CompareGO <- compareCluster(ClusterList, pvalueCutoff=1,readable=T, organism="mouse", pAdjustMethod="none", fun="enrichGO",ont="BP" )
> Sum<-summary(CompareGO)
> Sum[Sum$ID=="GO:0010498",1:4]
Cluster ID Description GeneRatio
544 1 GO:0010498 proteasomal protein catabolic process 7/372
5223 7 GO:0010498 proteasomal protein catabolic process 9/376
7136 9 GO:0010498 proteasomal protein catabolic process 7/668
> Sum[Sum$ID=="GO:0009790",1:4]
Cluster ID Description GeneRatio
860 2 GO:0009790 embryo development 66/600
2159 3 GO:0009790 embryo development 58/704
3185 5 GO:0009790 embryo development 62/556
4738 6 GO:0009790 embryo development 40/714
5580 7 GO:0009790 embryo development 18/376
5734 8 GO:0009790 embryo development 36/550
7121 9 GO:0009790 embryo development 31/668
I have 9 cluster in total, do you want to ClusterList object?
> sessionInfo()
R version 3.1.2 (2014-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8
[8] LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] tcltk grid parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] topGO_2.18.0 SparseM_1.6 graph_1.44.1 BiocInstaller_1.16.1 clusterProfiler_2.0.1 reactome.db_1.48.0 ReactomePA_1.10.1
[8] GO.db_3.0.0 org.Mm.eg.db_3.0.0 RSQLite_1.0.0 DBI_0.3.1 AnnotationDbi_1.28.1 Mfuzz_2.26.0 DynDoc_1.44.0
[15] widgetTools_1.44.0 e1071_1.6-4 Biobase_2.26.0 reshape2_1.4.1 Rsubread_1.16.1 biomaRt_2.22.0 wq_0.4-1
[22] zoo_1.7-11 reshape_0.8.5 ggplot2_1.0.0 RColorBrewer_1.1-2 DESeq2_1.6.3 RcppArmadillo_0.4.650.1.1 Rcpp_0.11.4
[29] GenomicRanges_1.18.4 GenomeInfoDb_1.2.4 IRanges_2.0.1 S4Vectors_0.4.0 BiocGenerics_0.12.1
loaded via a namespace (and not attached):
[1] acepack_1.3-3.3 annotate_1.44.0 base64enc_0.1-2 BatchJobs_1.5 BBmisc_1.9 BiocParallel_1.0.3 bitops_1.0-6 brew_1.0-6 checkmate_1.5.1
[10] class_7.3-12 cluster_2.0.1 codetools_0.2-10 colorspace_1.2-4 digest_0.6.8 DO.db_2.8.0 DOSE_2.4.0 fail_1.2 foreach_1.4.2
[19] foreign_0.8-63 Formula_1.2-0 genefilter_1.48.1 geneplotter_1.44.0 GOSemSim_1.24.1 graphite_1.12.0 gtable_0.1.2 Hmisc_3.15-0 igraph_0.7.1
[28] iterators_1.0.7 KEGG.db_3.0.0 labeling_0.3 lattice_0.20-30 latticeExtra_0.6-26 locfit_1.5-9.1 MASS_7.3-39 munsell_0.4.2 nnet_7.3-9
[37] org.Hs.eg.db_3.0.0 plyr_1.8.1 proto_0.3-10 qvalue_1.40.0 RCurl_1.95-4.5 rpart_4.1-9 scales_0.2.4 sendmailR_1.2-1 splines_3.1.2
[46] stringr_0.6.2 survival_2.38-1 tkWidgets_1.44.0 tools_3.1.2 XML_3.98-1.1 xtable_1.7-4 XVector_0.6.0
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Thanks that is what I thought :)
Thanks for the precision about minGSSize, I thought this was the min Size of the Gene set in the annotation (ie no GO therm are consider if they contain less than minGSSize genes).