Question: enrichGO (clusterProfiler) produces different results
0
gravatar for Javier Pérez Florido
21 months ago by
Javier Pérez Florido840 wrote:

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
ADD COMMENTlink modified 21 months ago by Guangchuang Yu1.1k • written 21 months ago by Javier Pérez Florido840
Answer: enrichGO (clusterProfiler) produces different results
1
gravatar for Guangchuang Yu
21 months ago by
Guangchuang Yu1.1k
China/Guangzhou/Southern Medical University
Guangchuang Yu1.1k wrote:

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).

ADD COMMENTlink written 21 months ago by Guangchuang Yu1.1k
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