Hello,

I am trying to analyse kallisto outputs with BioNERO package and have problems with module_trait_cor function. I create SummarizedExperiment with tximeta:

coldata <- data.frame(files, names=rownames(Np_samples), condition=Np_samples$Location, stringsAsFactors=FALSE)
se <- tximeta(coldata, typ="kallisto")

Following the vignette everything runs ok, until I proceed with module_trait_cor function, where I get:

MEtrait <- module_trait_cor(exp = final_exp, MEs = net$MEs)

# Error in cor(as.matrix(MEs), trait, use = "p", method = cor_method) :
# 'y' must be numeric

Any help would be appreciated. Please post if I need to post additional samples or code.

session_info() output:

R version 4.2.2 (2022-10-31) Platform: aarch64-apple-darwin20 (64-bit) Running under: macOS Ventura 13.5.1

Matrix products: default LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib

locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages: [1] stats4 stats graphics grDevices utils datasets methods base

other attached packages: [1] BioNERO_1.6.1 tximeta_1.16.1 palmerpenguins_0.1.1 DESeq2_1.38.3
[5] SummarizedExperiment_1.28.0 Biobase_2.58.0 MatrixGenerics_1.10.0 matrixStats_1.0.0
[9] GenomicRanges_1.50.2 GenomeInfoDb_1.34.9 IRanges_2.32.0 S4Vectors_0.36.2
[13] BiocGenerics_0.44.0 trinotateR_1.0 data.table_1.14.8 ggplot2_3.4.3
[17] tibble_3.2.1 janitor_2.2.0 tidyr_1.3.0 dplyr_1.1.2
[21] tximport_1.26.1

loaded via a namespace (and not attached): [1] rappdirs_0.3.3 rtracklayer_1.58.0 minet_3.56.0 coda_0.19-4
[5] bit64_4.0.5 knitr_1.43 DelayedArray_0.24.0 rpart_4.1.19
[9] KEGGREST_1.38.0 RCurl_1.98-1.12 AnnotationFilter_1.22.0 doParallel_1.0.17
[13] generics_0.1.3 preprocessCore_1.60.2 GenomicFeatures_1.50.4 RhpcBLASctl_0.23-42
[17] cowplot_1.1.1 microbiome_1.20.0 RSQLite_2.3.1 shadowtext_0.1.2
[21] bit_4.0.5 enrichplot_1.18.4 xml2_1.3.5 lubridate_1.9.2
[25] httpuv_1.6.11 viridis_0.6.4 xfun_0.40 hms_1.1.3
[29] evaluate_0.21 promises_1.2.1 fansi_1.0.4 restfulr_0.0.15
[33] progress_1.2.2 dbplyr_2.3.3 htmlwidgets_1.6.2 igraph_1.5.1
[37] DBI_1.1.3 geneplotter_1.76.0 purrr_1.0.2 ellipsis_0.3.2
[41] ggnewscale_0.4.9 ggpubr_0.6.0 backports_1.4.1 permute_0.9-7
[45] annotate_1.76.0 biomaRt_2.54.1 vctrs_0.6.3 Cairo_1.6-1
[49] ensembldb_2.22.0 abind_1.4-5 cachem_1.0.8 withr_2.5.0
[53] ggforce_0.4.1 HDO.db_0.99.1 checkmate_2.2.0 vegan_2.6-4
[57] GenomicAlignments_1.34.1 treeio_1.22.0 prettyunits_1.1.1 cluster_2.1.4
[61] DOSE_3.24.2 ape_5.7-1 lazyeval_0.2.2 crayon_1.5.2
[65] genefilter_1.80.3 labeling_0.4.2 edgeR_3.40.2 pkgconfig_2.0.3
[69] tweenr_2.0.2 nlme_3.1-163 ProtGenerics_1.30.0 nnet_7.3-19
[73] rlang_1.1.1 lifecycle_1.0.3 downloader_0.4 filelock_1.0.2
[77] BiocFileCache_2.6.1 phyloseq_1.42.0 AnnotationHub_3.6.0 polyclip_1.10-4
[81] Matrix_1.6-1 aplot_0.2.0 NetRep_1.2.7 carData_3.0-5
[85] Rhdf5lib_1.20.0 base64enc_0.1-3 GlobalOptions_0.1.2 png_0.1-8
[89] viridisLite_0.4.2 rjson_0.2.21 bitops_1.0-7 gson_0.1.0
[93] ggnetwork_0.5.12 rhdf5filters_1.10.1 Biostrings_2.66.0 blob_1.2.4
[97] shape_1.4.6 stringr_1.5.0 qvalue_2.30.0 rstatix_0.7.2
[101] gridGraphics_0.5-1 ggsignif_0.6.4 scales_1.2.1 memoise_2.0.1
[105] magrittr_2.0.3 plyr_1.8.8 zlibbioc_1.44.0 compiler_4.2.2
[109] scatterpie_0.2.1 BiocIO_1.8.0 RColorBrewer_1.1-3 intergraph_2.0-3
[113] clue_0.3-64 Rsamtools_2.14.0 snakecase_0.11.0 cli_3.6.1
[117] ade4_1.7-22 XVector_0.38.0 patchwork_1.1.3 htmlTable_2.4.1
[121] Formula_1.2-5 WGCNA_1.72-1 MASS_7.3-60 mgcv_1.9-0
[125] tidyselect_1.2.0 stringi_1.7.12 yaml_2.3.7 GOSemSim_2.24.0
[129] locfit_1.5-9.8 ggrepel_0.9.3 grid_4.2.2 fastmatch_1.1-4
[133] tools_4.2.2 timechange_0.2.0 parallel_4.2.2 circlize_0.4.15
[137] rstudioapi_0.15.0 foreign_0.8-84 foreach_1.5.2 gridExtra_2.3
[141] farver_2.1.1 Rtsne_0.16 ggraph_2.1.0 digest_0.6.33
[145] BiocManager_1.30.22 shiny_1.7.5 networkD3_0.4 Rcpp_1.0.11
[149] car_3.1-2 broom_1.0.5 BiocVersion_3.16.0 later_1.3.1
[153] httr_1.4.7 AnnotationDbi_1.60.2 ComplexHeatmap_2.14.0 GENIE3_1.20.0
[157] colorspace_2.1-0 XML_3.99-0.14 splines_4.2.2 yulab.utils_0.0.8
[161] statmod_1.5.0 tidytree_0.4.5 graphlayouts_1.0.0 multtest_2.54.0
[165] ggplotify_0.1.2 xtable_1.8-4 jsonlite_1.8.7 ggtree_3.6.2
[169] dynamicTreeCut_1.63-1 tidygraph_1.2.3 ggfun_0.1.2 R6_2.5.1
[173] Hmisc_5.1-0 pillar_1.9.0 htmltools_0.5.6 mime_0.12
[177] glue_1.6.2 fastmap_1.1.1 clusterProfiler_4.6.2 BiocParallel_1.32.6
[181] interactiveDisplayBase_1.36.0 codetools_0.2-19 fgsea_1.24.0 utf8_1.2.3
[185] sva_3.46.0 lattice_0.21-8 network_1.18.1 curl_5.0.2
[189] magick_2.7.5 GO.db_3.16.0 limma_3.54.2 survival_3.5-7
[193] rmarkdown_2.24 statnet.common_4.9.0 biomformat_1.26.0 munsell_0.5.0
[197] GetoptLong_1.0.5 fastcluster_1.2.3 rhdf5_2.42.1 GenomeInfoDbData_1.2.9
[201] iterators_1.0.14 impute_1.72.3 reshape2_1.4.4 gtable_0.3.4

The error message seems to be quite clear. It says

# Error in cor(as.matrix(MEs), trait, use = "p", method = cor_method) :
# 'y' must be numeric

You have an argument 'MEs' that you are passing into the function, and R is telling you that it's not numeric.