Problem with ORA in CEMiTool
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j.a.craft • 0
@c0c5a319
Last seen 3 months ago
United Kingdom

I am running CEMiTool with an RNAseq dataset. I am using CEMiTool v 1.18.1 with R 4.1.2. I have an abundance table with transcript quantities aligned with uniprot accession ids derived from the starting RefSeq mRNA identifiers with bioDBnet. I removed duplicates from the table and set the uniprot ids as rownames. The cemitool command below generated two modules although only one shows on the GSEA heatmap. By increasing the value of beta two modules show on the heatmap but one consists of genes that are not correlated. Based on the cem output with set beta =5 I have a problem with the Profile plot (see below) and also with the Over Representation Analysis (see below)

Code should be placed in three backticks as shown below


# ```cem<-cemitool(expr=test_df2, sample_annot2, set_beta=5, filter=TRUE, verbose=TRUE)

```sample_annotation(cem,

  • sample_name_column="SampleName",
  • class_column="Class") <- sample_annot2 #cem <- plot_profile(cem) plots <- show_plot(cem, "profile") plots[1]#Warning message: In grid.Call.graphics(C_rect, x$x, x$y, x$width, x$height, resolveHJust(x$just, : semi-transparency is not supported on this device: reported only once per page & #gmt_fname <- system.file("extdata", "pathways.gmt", package = "CEMiTool")

    gmt_in <- read_gmt(gmt_fname) cem <- mod_ora(cem, gmt_in) ```

    No gene can be mapped....

    --> Expected input gene ID: ABCC2,RPS13,PRPS2,RPS9,ABCA6,XRCC4 --> return NULL... --> No gene can be mapped.... --> Expected input gene ID: PEX19,ABCA3,ABCA12,EIF4E,NCAN,RPS10 --> return NULL... Warning messages: 1: In FUN(X[[i]], ...) : Enrichment for module M1 is NULL 2: In .local(cem, ...) : Enrichment is NULL. Either your gmt file is inadequate or your modules really aren't enriched for any of the pathways in the gmt file.

please also include the results of running the following in an R session

sessionInfo( ) R version 4.1.2 (2021-11-01) Platform: x86_64-pc-linux-gnu (64-bit) Running under: AlmaLinux 8.5 (Arctic Sphynx)

Matrix products: default BLAS: /opt/software/R/gcc-8.5.0/4.1.2/Xeon-6138/lib64/R/lib/libRblas.so LAPACK: /opt/software/R/gcc-8.5.0/4.1.2/Xeon-6138/lib64/R/lib/libRlapack.so

locale: [1] C

attached base packages: [1] stats graphics grDevices utils datasets methods base

other attached packages: [1] Cairo_1.6-0 RColorBrewer_1.1-3 CEMiTool_1.18.1 forcats_0.5.1
[5] stringr_1.4.0 dplyr_1.0.9 purrr_0.3.4 readr_2.1.2
[9] tidyr_1.2.0 tibble_3.1.6 ggplot2_3.3.5 tidyverse_1.3.1
[13] here_1.0.1

loaded via a namespace (and not attached): [1] utf8_1.2.2 tidyselect_1.1.2 RSQLite_2.2.13
[4] AnnotationDbi_1.56.2 htmlwidgets_1.5.4 grid_4.1.2
[7] BiocParallel_1.28.3 scatterpie_0.1.7 munsell_0.5.0
[10] codetools_0.2-18 preprocessCore_1.56.0 DT_0.22
[13] withr_2.5.0 colorspace_2.0-3 GOSemSim_2.20.0
[16] Biobase_2.54.0 highr_0.9 knitr_1.39
[19] rstudioapi_0.13 stats4_4.1.2 DOSE_3.20.1
[22] labeling_0.4.2 GenomeInfoDbData_1.2.7 polyclip_1.10-0
[25] bit64_4.0.5 farver_2.1.0 rprojroot_2.0.3
[28] downloader_0.4 coda_0.19-4 vctrs_0.4.1
[31] treeio_1.18.1 generics_0.1.2 xfun_0.30
[34] ggthemes_4.2.4 ggpmisc_0.4.6 fastcluster_1.2.3
[37] R6_2.5.1 doParallel_1.0.17 GenomeInfoDb_1.30.1
[40] graphlayouts_0.8.0 bitops_1.0-7 cachem_1.0.6
[43] fgsea_1.20.0 gridGraphics_0.5-1 assertthat_0.2.1
[46] scales_1.2.0 ggraph_2.0.5 nnet_7.3-17
[49] enrichplot_1.14.2 gtable_0.3.0 WGCNA_1.71
[52] tidygraph_1.2.1 rlang_1.0.2 MatrixModels_0.5-0
[55] splines_4.1.2 lazyeval_0.2.2 impute_1.68.0
[58] broom_0.8.0 checkmate_2.1.0 intergraph_2.0-2
[61] yaml_2.3.5 reshape2_1.4.4 modelr_0.1.8
[64] crosstalk_1.2.0 backports_1.4.1 qvalue_2.26.0
[67] Hmisc_4.7-0 clusterProfiler_4.2.2 tools_4.1.2
[70] ggplotify_0.1.0 statnet.common_4.6.0 ellipsis_0.3.2
[73] jquerylib_0.1.4 ggdendro_0.1.23 BiocGenerics_0.40.0
[76] dynamicTreeCut_1.63-1 polynom_1.4-1 Rcpp_1.0.8.3
[79] plyr_1.8.7 base64enc_0.1-3 zlibbioc_1.40.0
[82] RCurl_1.98-1.5 rpart_4.1.16 viridis_0.6.2
[85] S4Vectors_0.32.4 haven_2.5.0 ggrepel_0.9.1
[88] cluster_2.1.3 fs_1.5.2 magrittr_2.0.3
[91] data.table_1.14.2 sna_2.6 DO.db_2.9
[94] SparseM_1.81 reprex_2.0.1 matrixStats_0.62.0
[97] hms_1.1.1 patchwork_1.1.1 evaluate_0.15
[100] jpeg_0.1-9 readxl_1.4.0 IRanges_2.28.0
[103] gridExtra_2.3 compiler_4.1.2 crayon_1.5.1
[106] shadowtext_0.1.2 htmltools_0.5.2 mgcv_1.8-40
[109] ggfun_0.0.6 tzdb_0.3.0 Formula_1.2-4
[112] aplot_0.1.3 lubridate_1.8.0 DBI_1.1.2
[115] tweenr_1.0.2 dbplyr_2.1.1 MASS_7.3-57
[118] Matrix_1.4-1 cli_3.3.0 parallel_4.1.2
[121] igraph_1.3.1 pkgconfig_2.0.3 foreign_0.8-82
[124] xml2_1.3.3 foreach_1.5.2 ggtree_3.2.1
[127] bslib_0.3.1 XVector_0.34.0 ggpp_0.4.4
[130] rvest_1.0.2 yulab.utils_0.0.4 digest_0.6.29
[133] pracma_2.3.8 Biostrings_2.62.0 rmarkdown_2.14
[136] cellranger_1.1.0 fastmatch_1.1-3 tidytree_0.3.9
[139] htmlTable_2.4.0 quantreg_5.93 lifecycle_1.0.1
[142] nlme_3.1-157 jsonlite_1.8.0 network_1.17.1
[145] viridisLite_0.4.0 fansi_1.0.3 pillar_1.7.0
[148] lattice_0.20-45 KEGGREST_1.34.0 fastmap_1.1.0
[151] httr_1.4.2 survival_3.3-1 GO.db_3.14.0
[154] glue_1.6.2 png_0.1-7 iterators_1.0.14
[157] bit_4.0.4 ggforce_0.3.3 stringi_1.7.6
[160] sass_0.4.1 blob_1.2.3 latticeExtra_0.6-29
[163] memoise_2.0.1 ape_5.6-2 ```

GeneRegulation • 170 views
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