clusterProfiler
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YuLab-SMU
How to generate gseaplots from the result of compareCluster gseaGO or gseaKEGG functions?
We have ran the compareCluster gseaGO or gseaKEGG functions and there were three groups. Now we want to generate the gseaplot2 from the result, but after we ran the codes: gseaplot2(GO_sim_readable, geneSetID = c(10,61,213),pvalue_table = TRUE,color = c("#3C234A","#70BACC","#ECDC52"),), we got the error:
Error in FUN(X[[i]], ...) : no slot of name "geneList" for this object of class "compareClusterResult"
Hope to get your help. Thank you.
I can reproduce your 'error'. Reason for this is that results from a compareCluster analysis can not be handled by gseaplot2; see this part of the error message: no slot of name "geneList" for this object of class "compareClusterResult".
gseaplot2 only accepts results from a single GSEA run.
Yet, since the output from a compareCluster and GSEA run are very similar (the only differences are the rownames and addition of a column labelled Cluster in the former), it might be that this can be relatively easily implemented.
@huerqiang : could you please comment on this?
I can envision that when a compareCluster-GSEA result is used for gseaplot2, first a facet should be made based on geneSetID, and that then within each of these plots the results of the different clusters for this geneSetID are plotted.
> library(clusterProfiler)
> library(enrichplot)
>
> library(org.Hs.eg.db)
>
> data(geneList, package="DOSE")
> inputList <- list(rankedGenes1 = geneList, rankedGenes2 = geneList)
>
> ## compareCluster-GSEA
> xx <- compareCluster(geneClusters=inputList, fun = "gseGO",
+ OrgDb = org.Hs.eg.db, keyType = "ENTREZID",
+ ont = "BP", eps = 0, pvalueCutoff = 0.05,
+ pAdjustMethod = "none", minGSSize = 10, maxGSSize = 500)
> xx <- enrichplot::pairwise_termsim(xx)
> xx <- setReadable(xx, 'org.Hs.eg.db', 'ENTREZID')
>
>
> gseaplot2(xx, geneSetID = c(1,2,3))
Error in FUN(X[[i]], ...) :
no slot of name "geneList" for this object of class "compareClusterResult"
>
>
> ## 'single' GSEA run
> yy <- gseGO(geneList, OrgDb = org.Hs.eg.db, keyType = "ENTREZID",
+ ont = "BP", eps = 0, pvalueCutoff = 0.05,
+ pAdjustMethod = "none", minGSSize = 10, maxGSSize = 500)
preparing geneSet collections...
GSEA analysis...
leading edge analysis...
done...
> yy <- enrichplot::pairwise_termsim(yy)
> yy <- setReadable(yy, 'org.Hs.eg.db', 'ENTREZID')
>
> gseaplot2(yy, geneSetID = c(1,2,3))
>
> ## check similarity output of both functions
> # compareCluster
> head(as.data.frame(xx))
Cluster ID Description setSize
1 rankedGenes1 GO:0007059 chromosome segregation 316
2 rankedGenes1 GO:0051276 chromosome organization 470
3 rankedGenes1 GO:0098813 nuclear chromosome segregation 236
4 rankedGenes1 GO:0000819 sister chromatid segregation 184
5 rankedGenes1 GO:0000070 mitotic sister chromatid segregation 151
6 rankedGenes1 GO:0000280 nuclear division 325
enrichmentScore NES pvalue p.adjust qvalue rank
1 0.5880591 2.772525 5.226983e-31 5.226983e-31 2.420368e-27 449
2 0.5189587 2.547566 1.140612e-30 1.140612e-30 2.640818e-27 1374
3 0.6307606 2.869422 1.517388e-29 1.517388e-29 2.342101e-26 449
4 0.6542189 2.872470 6.351943e-26 6.351943e-26 7.353210e-23 532
5 0.6795449 2.880584 8.909573e-25 8.909573e-25 8.251203e-22 532
6 0.5411728 2.565130 2.602072e-24 2.602072e-24 2.008161e-21 1246
leading_edge
1 tags=20%, list=4%, signal=20%
2 tags=24%, list=11%, signal=22%
3 tags=22%, list=4%, signal=22%
4 tags=25%, list=4%, signal=24%
5 tags=28%, list=4%, signal=28%
6 tags=26%, list=10%, signal=24%
core_enrichment
1 CDCA8/CDC20/KIF23/CENPE/MYBL2/CCNB2/NDC80/TOP2A/NCAPH/ASPM/DLGAP5/UBE2C/HJURP/SKA1/NUSAP1/TPX2/TACC3/NEK2/CENPM/CENPN/CDK1/MAD2L1/KIF18A/CDT1/BIRC5/KIF11/TTK/NCAPG/AURKB/TRIP13/PRC1/KIFC1/KIF18B/AURKA/CCNB1/KIF4A/PTTG1/KIF14/KIF2C/CDC6/PLK1/RACGAP1/PTTG3P/BUB1B/ZWINT/CENPU/SPC25/SPAG5/ECT2/CENPI/ESPL1/CCNE1/OIP5/MKI67/HAUS6/CCNE2/GPSM2/NCAPD2/BUB1/STIL/CENPF/FBXO5/ZWILCH
2 CDC45/CDCA8/CDC20/KIF23/CENPE/MYBL2/NDC80/TOP2A/NCAPH/DLGAP5/UBE2C/HJURP/NUSAP1/TPX2/TACC3/NEK2/CENPN/CDK1/MAD2L1/GINS1/KIF18A/CDT1/BIRC5/KIF11/EZH2/TTK/NCAPG/AURKB/GINS2/TRIP13/PRC1/KIFC1/KIF18B/CCNB1/KIF4A/MCM5/PTTG1/MCM2/KIF14/KIF2C/CDC6/PLK1/RACGAP1/PTTG3P/BUB1B/EXO1/ZWINT/SPC25/SPAG5/HMGA1/DSCC1/CENPI/RAD54L/ESPL1/RAD51/CCNE1/HMGB3/OIP5/CCNE2/MCM6/MCM4/FEN1/CCT5/RFC4/NCAPD2/CENPA/GINS4/BUB1/MYC/CENPF/PCNA/GINS3/RECQL4/FBXO5/ZWILCH/BLM/DNA2/NCAPG2/H3C10/H1-1/MCM7/HMGB2/DSN1/H1-2/MSH2/RFC2/KNTC1/CCT6A/NCAPD3/RUVBL1/H1-4/SMC4/CCT2/H1-5/MCM3/NUP155/BRIP1/RAD21/CHEK2/ERCC4/PSRC1/RMDN1/TUBG1/RFC3/NASP/PRKCQ/SPDL1/SMC2/UCHL5/NBN/MIS18A
3 CDCA8/CDC20/KIF23/CENPE/MYBL2/CCNB2/NDC80/TOP2A/NCAPH/ASPM/DLGAP5/UBE2C/NUSAP1/TPX2/TACC3/NEK2/CDK1/MAD2L1/KIF18A/CDT1/BIRC5/KIF11/TTK/NCAPG/AURKB/TRIP13/PRC1/KIFC1/KIF18B/AURKA/CCNB1/KIF4A/PTTG1/KIF14/KIF2C/CDC6/PLK1/RACGAP1/PTTG3P/BUB1B/ZWINT/SPC25/SPAG5/ECT2/CENPI/ESPL1/CCNE1/CCNE2/NCAPD2/BUB1/CENPF/FBXO5/ZWILCH
4 CDCA8/CDC20/KIF23/CENPE/MYBL2/NDC80/TOP2A/NCAPH/DLGAP5/UBE2C/NUSAP1/TPX2/TACC3/NEK2/CDK1/MAD2L1/KIF18A/CDT1/BIRC5/KIF11/TTK/NCAPG/AURKB/TRIP13/PRC1/KIFC1/KIF18B/CCNB1/KIF4A/KIF14/KIF2C/CDC6/PLK1/RACGAP1/BUB1B/ZWINT/SPC25/SPAG5/CENPI/ESPL1/NCAPD2/BUB1/CENPF/FBXO5/ZWILCH/NCAPG2
5 CDCA8/CDC20/KIF23/CENPE/MYBL2/NDC80/NCAPH/DLGAP5/UBE2C/NUSAP1/TPX2/NEK2/CDK1/MAD2L1/KIF18A/CDT1/BIRC5/KIF11/TTK/NCAPG/AURKB/TRIP13/PRC1/KIFC1/KIF18B/CCNB1/KIF4A/KIF14/KIF2C/PLK1/RACGAP1/BUB1B/ZWINT/SPC25/SPAG5/CENPI/ESPL1/NCAPD2/BUB1/CENPF/FBXO5/ZWILCH/NCAPG2
6 CDCA8/CDC20/KIF23/CENPE/MYBL2/CCNB2/NDC80/TOP2A/NCAPH/ASPM/DLGAP5/UBE2C/NUSAP1/TPX2/NEK2/RAD51AP1/UBE2S/CDK1/MAD2L1/KIF18A/CDT1/BIRC5/KIF11/TTK/NCAPG/AURKB/CHEK1/TRIP13/PRC1/KIFC1/KIF18B/AURKA/CCNB1/KIF4A/PTTG1/KIF14/CKS2/KIF2C/MYBL1/PLK1/RACGAP1/PTTG3P/BUB1B/ZWINT/SPC25/SPAG5/CENPI/RAD54L/ESPL1/RAD51/CCNE1/MKI67/CCNE2/FANCA/TDRD12/CDC25B/NCAPD2/BUB1/CENPF/FBXO5/ZWILCH/NCAPG2/RANBP1/DSN1/KIF20B/KNTC1/NCAPD3/FGF8/SPHK1/PKMYT1/CDC25C/SMC4/TOP6BL/RCC1/BORA/BRIP1/RAD21/CHEK2/ERCC4/CD28/DMRT1/PSRC1/RMDN1/TUBG1/RMI1
>
> # single GSEA run
> head(as.data.frame(yy))
ID Description setSize
GO:0051276 GO:0051276 chromosome organization 470
GO:0007059 GO:0007059 chromosome segregation 316
GO:0098813 GO:0098813 nuclear chromosome segregation 236
GO:0000819 GO:0000819 sister chromatid segregation 184
GO:0000280 GO:0000280 nuclear division 325
GO:0000070 GO:0000070 mitotic sister chromatid segregation 151
enrichmentScore NES pvalue p.adjust qvalue rank
GO:0051276 0.5189587 2.522024 2.379678e-31 2.379678e-31 1.085634e-27 1374
GO:0007059 0.5880591 2.784593 1.140483e-30 1.140483e-30 2.601503e-27 449
GO:0098813 0.6307606 2.893022 6.983985e-29 6.983985e-29 1.062056e-25 449
GO:0000819 0.6542189 2.916509 1.996114e-26 1.996114e-26 2.276620e-23 532
GO:0000280 0.5411728 2.580962 1.170368e-24 1.170368e-24 1.067869e-21 1246
GO:0000070 0.6795449 2.992971 2.273006e-24 2.273006e-24 1.728282e-21 532
leading_edge
GO:0051276 tags=24%, list=11%, signal=22%
GO:0007059 tags=20%, list=4%, signal=20%
GO:0098813 tags=22%, list=4%, signal=22%
GO:0000819 tags=25%, list=4%, signal=24%
GO:0000280 tags=26%, list=10%, signal=24%
GO:0000070 tags=28%, list=4%, signal=28%
core_enrichment
GO:0051276 CDC45/CDCA8/CDC20/KIF23/CENPE/MYBL2/NDC80/TOP2A/NCAPH/DLGAP5/UBE2C/HJURP/NUSAP1/TPX2/TACC3/NEK2/CENPN/CDK1/MAD2L1/GINS1/KIF18A/CDT1/BIRC5/KIF11/EZH2/TTK/NCAPG/AURKB/GINS2/TRIP13/PRC1/KIFC1/KIF18B/CCNB1/KIF4A/MCM5/PTTG1/MCM2/KIF14/KIF2C/CDC6/PLK1/RACGAP1/PTTG3P/BUB1B/EXO1/ZWINT/SPC25/SPAG5/HMGA1/DSCC1/CENPI/RAD54L/ESPL1/RAD51/CCNE1/HMGB3/OIP5/CCNE2/MCM6/MCM4/FEN1/CCT5/RFC4/NCAPD2/CENPA/GINS4/BUB1/MYC/CENPF/PCNA/GINS3/RECQL4/FBXO5/ZWILCH/BLM/DNA2/NCAPG2/H3C10/H1-1/MCM7/HMGB2/DSN1/H1-2/MSH2/RFC2/KNTC1/CCT6A/NCAPD3/RUVBL1/H1-4/SMC4/CCT2/H1-5/MCM3/NUP155/BRIP1/RAD21/CHEK2/ERCC4/PSRC1/RMDN1/TUBG1/RFC3/NASP/PRKCQ/SPDL1/SMC2/UCHL5/NBN/MIS18A
GO:0007059 CDCA8/CDC20/KIF23/CENPE/MYBL2/CCNB2/NDC80/TOP2A/NCAPH/ASPM/DLGAP5/UBE2C/HJURP/SKA1/NUSAP1/TPX2/TACC3/NEK2/CENPM/CENPN/CDK1/MAD2L1/KIF18A/CDT1/BIRC5/KIF11/TTK/NCAPG/AURKB/TRIP13/PRC1/KIFC1/KIF18B/AURKA/CCNB1/KIF4A/PTTG1/KIF14/KIF2C/CDC6/PLK1/RACGAP1/PTTG3P/BUB1B/ZWINT/CENPU/SPC25/SPAG5/ECT2/CENPI/ESPL1/CCNE1/OIP5/MKI67/HAUS6/CCNE2/GPSM2/NCAPD2/BUB1/STIL/CENPF/FBXO5/ZWILCH
GO:0098813 CDCA8/CDC20/KIF23/CENPE/MYBL2/CCNB2/NDC80/TOP2A/NCAPH/ASPM/DLGAP5/UBE2C/NUSAP1/TPX2/TACC3/NEK2/CDK1/MAD2L1/KIF18A/CDT1/BIRC5/KIF11/TTK/NCAPG/AURKB/TRIP13/PRC1/KIFC1/KIF18B/AURKA/CCNB1/KIF4A/PTTG1/KIF14/KIF2C/CDC6/PLK1/RACGAP1/PTTG3P/BUB1B/ZWINT/SPC25/SPAG5/ECT2/CENPI/ESPL1/CCNE1/CCNE2/NCAPD2/BUB1/CENPF/FBXO5/ZWILCH
GO:0000819 CDCA8/CDC20/KIF23/CENPE/MYBL2/NDC80/TOP2A/NCAPH/DLGAP5/UBE2C/NUSAP1/TPX2/TACC3/NEK2/CDK1/MAD2L1/KIF18A/CDT1/BIRC5/KIF11/TTK/NCAPG/AURKB/TRIP13/PRC1/KIFC1/KIF18B/CCNB1/KIF4A/KIF14/KIF2C/CDC6/PLK1/RACGAP1/BUB1B/ZWINT/SPC25/SPAG5/CENPI/ESPL1/NCAPD2/BUB1/CENPF/FBXO5/ZWILCH/NCAPG2
GO:0000280 CDCA8/CDC20/KIF23/CENPE/MYBL2/CCNB2/NDC80/TOP2A/NCAPH/ASPM/DLGAP5/UBE2C/NUSAP1/TPX2/NEK2/RAD51AP1/UBE2S/CDK1/MAD2L1/KIF18A/CDT1/BIRC5/KIF11/TTK/NCAPG/AURKB/CHEK1/TRIP13/PRC1/KIFC1/KIF18B/AURKA/CCNB1/KIF4A/PTTG1/KIF14/CKS2/KIF2C/MYBL1/PLK1/RACGAP1/PTTG3P/BUB1B/ZWINT/SPC25/SPAG5/CENPI/RAD54L/ESPL1/RAD51/CCNE1/MKI67/CCNE2/FANCA/TDRD12/CDC25B/NCAPD2/BUB1/CENPF/FBXO5/ZWILCH/NCAPG2/RANBP1/DSN1/KIF20B/KNTC1/NCAPD3/FGF8/SPHK1/PKMYT1/CDC25C/SMC4/TOP6BL/RCC1/BORA/BRIP1/RAD21/CHEK2/ERCC4/CD28/DMRT1/PSRC1/RMDN1/TUBG1/RMI1
GO:0000070 CDCA8/CDC20/KIF23/CENPE/MYBL2/NDC80/NCAPH/DLGAP5/UBE2C/NUSAP1/TPX2/NEK2/CDK1/MAD2L1/KIF18A/CDT1/BIRC5/KIF11/TTK/NCAPG/AURKB/TRIP13/PRC1/KIFC1/KIF18B/CCNB1/KIF4A/KIF14/KIF2C/PLK1/RACGAP1/BUB1B/ZWINT/SPC25/SPAG5/CENPI/ESPL1/NCAPD2/BUB1/CENPF/FBXO5/ZWILCH/NCAPG2
>
Thank you for your answer. I agree with you on that. As the output formats from compreCluster and gseGO are quite similar with only the difference in the cluster column, (1) Is it possible to split the output from compareCluster to individual gseGO so that we can plot figures as we do with gseGO output? It takes time to run gseGO again and sometimes the results are not exactly the same as that from compareCluster due to some parameter differences. (2) Or can you add the function to plot the compareCluster output directly? Thank you very much.