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Describe the bug
I am trying to use the olink_pathway_enrichment function however some assays are identified as not found in the database and they are excluded from the analysis. I'm trying also with data from the Immuno-Oncology Panel by I get the same error
Hi @StheBerga depending on the Olink product and Ontology some assays may not be found. We have found that by removing "-" from the assays most assays will be located although there are some that need to be manually mapped. If you email us with the remaining assays we can send a mapping file to help.
Describe the bug
I am trying to use the olink_pathway_enrichment function however some assays are identified as not found in the database and they are excluded from the analysis. I'm trying also with data from the Immuno-Oncology Panel by I get the same error
To Reproduce
npx_df <- npx_data1
npx_df <- npx_df[!grepl("control", npx_df$SampleID, ignore.case = TRUE),]
ttest_results <- olink_ttest(
df = npx_df,
variable = "Treatment",
alternative = "two.sided")
gsea_results <- olink_pathway_enrichment(data = npx_data1, test_results = ttest_results)
Screenshots
System Information:
R version 4.3.3 (2024-02-29 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 11 x64 (build 22631)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8 LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
time zone: Europe/Rome
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] OlinkAnalyze_3.8.2
loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 rstudioapi_0.16.0 jsonlite_1.8.8
[4] magrittr_2.0.3 TH.data_1.1-2 estimability_1.5.1
[7] farver_2.1.2 nloptr_2.1.1 fs_1.6.4
[10] zlibbioc_1.48.2 vctrs_0.6.5 memoise_2.0.1
[13] minqa_1.2.7 RCurl_1.98-1.16 ggtree_3.10.1
[16] rstatix_0.7.2 forcats_1.0.0 broom_1.0.6
[19] cellranger_1.1.0 gridGraphics_0.5-1 plyr_1.8.9
[22] sandwich_3.1-0 emmeans_1.10.4 zoo_1.8-12
[25] cachem_1.1.0 igraph_2.0.3 lifecycle_1.0.4
[28] pkgconfig_2.0.3 gson_0.1.0 Matrix_1.6-5
[31] R6_2.5.1 fastmap_1.2.0 GenomeInfoDbData_1.2.11
[34] digest_0.6.36 numDeriv_2016.8-1.1 aplot_0.2.3
[37] enrichplot_1.22.0 colorspace_2.1-0 patchwork_1.2.0
[40] AnnotationDbi_1.64.1 S4Vectors_0.40.2 RSQLite_2.3.7
[43] fansi_1.0.6 httr_1.4.7 polyclip_1.10-7
[46] abind_1.4-5 compiler_4.3.3 bit64_4.0.5
[49] withr_3.0.1 backports_1.5.0 BiocParallel_1.36.0
[52] carData_3.0-5 viridis_0.6.5 DBI_1.2.3
[55] ggforce_0.4.2 MASS_7.3-60.0.1 HDO.db_0.99.1
[58] tools_4.3.3 ape_5.8 scatterpie_0.2.3
[61] msigdbr_7.5.1 zip_2.3.1 glue_1.7.0
[64] nlme_3.1-166 GOSemSim_2.28.1 shadowtext_0.1.4
[67] grid_4.3.3 reshape2_1.4.4 snow_0.4-4
[70] fgsea_1.28.0 generics_0.1.3 gtable_0.3.5
[73] tidyr_1.3.1 data.table_1.15.4 tidygraph_1.3.1
[76] car_3.1-2 utf8_1.2.4 XVector_0.42.0
[79] BiocGenerics_0.48.1 ggrepel_0.9.5 pillar_1.9.0
[82] stringr_1.5.1 babelgene_22.9 yulab.utils_0.1.7
[85] splines_4.3.3 dplyr_1.1.4 tweenr_2.0.3
[88] treeio_1.26.0 lattice_0.22-6 survival_3.7-0
[91] bit_4.0.5 tidyselect_1.2.1 GO.db_3.18.0
[94] Biostrings_2.70.3 gridExtra_2.3 IRanges_2.36.0
[97] stats4_4.3.3 graphlayouts_1.1.1 Biobase_2.62.0
[100] stringi_1.8.4 lazyeval_0.2.2 ggfun_0.1.5
[103] boot_1.3-30 codetools_0.2-20 ggraph_2.2.1
[106] tibble_3.2.1 qvalue_2.34.0 ggplotify_0.1.2
[109] cli_3.6.2 xtable_1.8-4 munsell_0.5.1
[112] Rcpp_1.0.13 GenomeInfoDb_1.38.8 readxl_1.4.3
[115] png_0.1-8 parallel_4.3.3 ggplot2_3.5.1
[118] blob_1.2.4 clusterProfiler_4.10.1 DOSE_3.28.2
[121] bitops_1.0-8 lme4_1.1-35.5 viridisLite_0.4.2
[124] mvtnorm_1.2-5 tidytree_0.4.6 lmerTest_3.1-3
[127] scales_1.3.0 purrr_1.0.2 crayon_1.5.3
[130] rlang_1.1.3 cowplot_1.1.3 fastmatch_1.1-4
[133] KEGGREST_1.42.0 multcomp_1.4-26
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