enrichGO (clusterProfiler) produces different results
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Entering edit mode
@javier-perez-florido-3121
Last seen 3.5 years ago

I'm using enrichGO function from clusterProfiler package to run a functional enrichment analysis using a set of annotated peaks from a chip-seq experiment (the input is the list of genes obtained by the annotation of peaks, human).

Using the same input data, I'm getting different results from enrichGO function using the latest version when compared to a previous one from beginning 2017. From the older version, I get much more GO terms, with a count value very high for each term (for example, biological process appears as enriched) and now I get less GO terms with a count value quite low. I didn't change function parameters. It seems like now more specific GO terms are returned instead of all enriched terms regardless of the level of GO hierarchy. What was the change in the behavior of enrichGO function?

Thanks,

Javier

> sessionInfo()

R version 3.4.3 (2017-11-30)

Platform: x86_64-redhat-linux-gnu (64-bit)

Running under: CentOS Linux 7 (Core)

Matrix products: default

BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so

locale:

 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              

 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    

 [5] LC_MONETARY=es_ES.UTF-8    LC_MESSAGES=en_US.UTF-8   

 [7] LC_PAPER=es_ES.UTF-8       LC_NAME=C                 

 [9] LC_ADDRESS=C               LC_TELEPHONE=C            

[11] LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C       

attached base packages:

[1] stats4    parallel  stats     graphics  grDevices utils     datasets

[8] methods   base     

other attached packages:

 [1] clusterProfiler_3.6.0                  

 [2] DOSE_3.4.0                             

 [3] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2

 [4] GenomicFeatures_1.30.3                 

 [5] AnnotationDbi_1.40.0                   

 [6] Biobase_2.38.0                         

 [7] GenomicRanges_1.30.3                   

 [8] GenomeInfoDb_1.14.0                    

 [9] IRanges_2.12.0                         

[10] S4Vectors_0.16.0                       

[11] BiocGenerics_0.24.0                    

[12] ChIPseeker_1.14.2                      

loaded via a namespace (and not attached):

 [1] httr_1.3.1                 tidyr_0.8.0               

 [3] RMySQL_0.10.14             bit64_0.9-7               

 [5] splines_3.4.3              gtools_3.5.0              

 [7] assertthat_0.2.0           DO.db_2.9                 

 [9] rvcheck_0.0.9              blob_1.1.0                

[11] GenomeInfoDbData_1.0.0     Rsamtools_1.30.0          

[13] progress_1.1.2             pillar_1.2.1              

[15] RSQLite_2.0                lattice_0.20-35           

[17] glue_1.2.0                 digest_0.6.15             

[19] RColorBrewer_1.1-2         XVector_0.18.0            

[21] qvalue_2.10.0              colorspace_1.3-2          

[23] Matrix_1.2-12              plyr_1.8.4                

[25] XML_3.98-1.10              pkgconfig_2.0.1           

[27] biomaRt_2.34.2             zlibbioc_1.24.0           

[29] purrr_0.2.4                GO.db_3.5.0               

[31] scales_0.5.0               gdata_2.18.0              

[33] BiocParallel_1.12.0        tibble_1.4.2              

[35] ggplot2_2.2.1              UpSetR_1.3.3              

[37] SummarizedExperiment_1.8.1 lazyeval_0.2.1            

[39] magrittr_1.5               memoise_1.1.0             

[41] gplots_3.0.1               tools_3.4.3               

[43] data.table_1.10.4-3        prettyunits_1.0.2         

[45] gridBase_0.4-7             matrixStats_0.53.1        

[47] stringr_1.3.0              munsell_0.4.3             

[49] plotrix_3.7                DelayedArray_0.4.1        

[51] bindrcpp_0.2               Biostrings_2.46.0         

[53] compiler_3.4.3             caTools_1.17.1            

[55] rlang_0.2.0                grid_3.4.3                

[57] RCurl_1.95-4.10            igraph_1.2.1              

[59] bitops_1.0-6               boot_1.3-20               

[61] gtable_0.2.0               DBI_0.8                   

[63] reshape2_1.4.3             R6_2.2.2                  

[65] GenomicAlignments_1.14.1   gridExtra_2.3             

[67] dplyr_0.7.4                rtracklayer_1.38.3        

[69] bit_1.1-12                 bindr_0.1.1               

[71] fastmatch_1.1-0            fgsea_1.4.1               

[73] KernSmooth_2.23-15         GOSemSim_2.4.1            

[75] stringi_1.1.7              Rcpp_0.12.16
chipseq go enrichment clusterprofiler • 539 views
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1
Entering edit mode
Guangchuang Yu ★ 1.2k
@guangchuang-yu-5419
Last seen 7 months ago
China/Guangzhou/Southern Medical Univer…

The old version of clusterProfiler has a bug as it take all genes with GO annotation as background. This is why ‘biological process’ can be enriched.

This bug has been fixed 1 years ago, and now enrichGO only take all genes with specify sub-GO ontology annotation (e.g. BP).

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