Not getting any Kme (NaN) values after "ModuleConnectivity"

[Paoloorder66]

Describe the bug After running the MolduleConnectivity function all the Kme values are 0. I do not get any errors. I have me and hme values.

Steps to reproduce I am following along from the introduction vignette using my own dataset. I ran all of the standard seurat functions on the data (removed dead, scaled normalize, vst, pca, UMAP, DEGs, etc). Have not tried to reproduce the error on a tutorial dataset.

EM <- SetupForWGCNA(
  EM,
  gene_select = "fraction", # the gene selection approach
  fraction = 0.05, # fraction of cells that a gene needs to be expressed in order to be included
  wgcna_name = "EM_WGCNA" # the name of the hdWGCNA experiment
)

# construct metacells  in each group
EM <- MetacellsByGroups(
  EM,
  group.by = c("sample_group"), # specify the columns in [email protected] to group by
  reduction = 'harmony', # select the dimensionality reduction to perform KNN on
  k = 25, # nearest-neighbors parameter
  min_cells = 100,
  max_shared = 10, # maximum number of shared cells between two metacells
  ident.group = 'sample_group' # set the Idents of the metacell seurat object
)

# normalize metacell expression matrix:
EM <- NormalizeMetacells(EM)


EM <- SetDatExpr(
  EM,
  group_name = c("EM1", "EM2", "EM3"),
  group.by='sample_group',
  assay = 'RNA', # using RNA assay
  slot = 'data' # using normalized data
)


# Test different soft powers:
EM <- TestSoftPowers(
  EM,
  networkType = 'signed' # you can also use "unsigned" or "signed hybrid"
)

# plot the results:
plot_list <- PlotSoftPowers(EM)

# assemble with patchwork
wrap_plots(plot_list, ncol=2)


# construct co-expression network:
EM <- ConstructNetwork(
  EM,
  tom_name = 'sample_group' # name of the topoligical overlap matrix written to disk
) 

PlotDendrogram(EM, main='group hdWGCNA Dendrogram') (I see a dendrogram with various modules


# compute all MEs in the full single-cell dataset
EM <- ModuleEigengenes(
 EM,
 group.by.vars="donor"
)

# harmonized module eigengenes:
hMEs <- GetMEs(EM)

# module eigengenes:
MEs <- GetMEs(EM, harmonized=FALSE)


# compute eigengene-based connectivity (kME):
EM <- ModuleConnectivity(
  EM,
  group.by = 'sample_group'
)

> head(modules[,1:6])
          gene_name module  color kME_grey kME_EM-M1 kME_EM-M2
LINC01409 LINC01409   grey   grey      NaN       NaN       NaN
LINC01128 LINC01128  EM-M1   pink      NaN       NaN       NaN
NOC2L         NOC2L   grey   grey      NaN       NaN       NaN
HES4           HES4   grey   grey      NaN       NaN       NaN
ISG15         ISG15  EM-M2 yellow      NaN       NaN       NaN
C1orf159   C1orf159   grey   grey      NaN       NaN       NaN

I also tried plotting with the following but, of course, nothing was there

p <- PlotKMEs(EM, ncol=5)

p

R session info sessionInfo() R version 4.4.0 (2024-04-24) Platform: x86_64-apple-darwin20 Running under: macOS Monterey 12.6.3

Matrix products: default BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib LAPACK: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0

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

time zone: America/New_York tzcode source: internal

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

other attached packages: [1] UCell_2.8.0 hdWGCNA_0.3.03 igraph_2.0.3 ggrepel_0.9.5 WGCNA_1.72-5 fastcluster_1.2.6 dynamicTreeCut_1.63-1 cowplot_1.1.3 harmony_1.2.0
[10] Rcpp_1.0.12 lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 purrr_1.0.2 readr_2.1.5 tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.1
[19] tidyverse_2.0.0 patchwork_1.2.0 dplyr_1.1.4 Seurat_5.1.0 SeuratObject_5.0.2 sp_2.1-4

loaded via a namespace (and not attached): [1] fs_1.6.4 matrixStats_1.3.0 spatstat.sparse_3.0-3 devtools_2.4.5 httr_1.4.7 RColorBrewer_1.1-3 doParallel_1.0.17
[8] profvis_0.3.8 tools_4.4.0 sctransform_0.4.1 backports_1.5.0 utf8_1.2.4 R6_2.5.1 lazyeval_0.2.2
[15] uwot_0.2.2 urlchecker_1.0.1 withr_3.0.0 gridExtra_2.3 preprocessCore_1.66.0 progressr_0.14.0 cli_3.6.2
[22] Biobase_2.64.0 textshaping_0.4.0 spatstat.explore_3.2-7 fastDummies_1.7.3 labeling_0.4.3 spatstat.data_3.0-4 proxy_0.4-27
[29] ggridges_0.5.6 pbapply_1.7-2 systemfonts_1.1.0 foreign_0.8-86 parallelly_1.37.1 sessioninfo_1.2.2 rstudioapi_0.16.0
[36] impute_1.78.0 RSQLite_2.3.7 FNN_1.1.4 generics_0.1.3 ica_1.0-3 spatstat.random_3.2-3 GO.db_3.19.1
[43] Matrix_1.7-0 fansi_1.0.6 S4Vectors_0.42.0 abind_1.4-5 lifecycle_1.0.4 yaml_2.3.8 SummarizedExperiment_1.34.0 [50] SparseArray_1.4.8 Rtsne_0.17 grid_4.4.0 blob_1.2.4 promises_1.3.0 crayon_1.5.2 miniUI_0.1.1.1
[57] lattice_0.22-6 KEGGREST_1.44.0 pillar_1.9.0 knitr_1.47 GenomicRanges_1.56.0 future.apply_1.11.2 codetools_0.2-20
[64] leiden_0.4.3.1 glue_1.7.0 data.table_1.15.4 remotes_2.5.0 vctrs_0.6.5 png_0.1-8 spam_2.10-0
[71] gtable_0.3.5 cachem_1.1.0 xfun_0.44 S4Arrays_1.4.1 mime_0.12 survival_3.6-4 SingleCellExperiment_1.26.0 [78] iterators_1.0.14 ellipsis_0.3.2 fitdistrplus_1.1-11 ROCR_1.0-11 nlme_3.1-164 usethis_2.2.3 bit64_4.0.5
[85] RcppAnnoy_0.0.22 GenomeInfoDb_1.40.1 irlba_2.3.5.1 KernSmooth_2.23-24 rpart_4.1.23 colorspace_2.1-0 BiocGenerics_0.50.0
[92] DBI_1.2.2 Hmisc_5.1-3 nnet_7.3-19 tidyselect_1.2.1 bit_4.0.5 compiler_4.4.0 htmlTable_2.4.2
[99] BiocNeighbors_1.22.0 DelayedArray_0.30.1 plotly_4.10.4 checkmate_2.3.1 scales_1.3.0 lmtest_0.9-40 digest_0.6.35
[106] goftest_1.2-3 spatstat.utils_3.0-4 presto_1.0.0 rmarkdown_2.27 XVector_0.44.0 RhpcBLASctl_0.23-42 htmltools_0.5.8.1
[113] pkgconfig_2.0.3 base64enc_0.1-3 MatrixGenerics_1.16.0 fastmap_1.2.0 rlang_1.1.4 htmlwidgets_1.6.4 UCSC.utils_1.0.0
[120] shiny_1.8.1.1 farver_2.1.2 zoo_1.8-12 jsonlite_1.8.8 BiocParallel_1.38.0 magrittr_2.0.3 Formula_1.2-5
[127] GenomeInfoDbData_1.2.12 dotCall64_1.1-1 munsell_0.5.1 viridis_0.6.5 reticulate_1.37.0 stringi_1.8.4 zlibbioc_1.50.0
[134] MASS_7.3-60.2 plyr_1.8.9 pkgbuild_1.4.4 parallel_4.4.0 listenv_0.9.1 deldir_2.0-4 Biostrings_2.70.3
[141] splines_4.4.0 tensor_1.5 hms_1.1.3 spatstat.geom_3.2-9 RcppHNSW_0.6.0 reshape2_1.4.4 stats4_4.4.0
[148] pkgload_1.3.4 evaluate_0.23 tester_0.2.0 BiocManager_1.30.23 tzdb_0.4.0 foreach_1.5.2 httpuv_1.6.15
[155] RANN_2.6.1 polyclip_1.10-6 future_1.33.2 scattermore_1.2 xtable_1.8-4 RSpectra_0.16-1 later_1.3.2
[162] viridisLite_0.4.2 ragg_1.3.2 memoise_2.0.1 AnnotationDbi_1.66.0 IRanges_2.38.0 cluster_2.1.6 timechange_0.3.0
[169] globals_0.16.3

[smorabit]

Hi, thank you for taking the time to write this issue.

Have not tried to reproduce the error on a tutorial dataset.

I have never personally run into this issue in any of my testing, and I need to be able to reproduce your error in order to help resolve it. Please let me know if you get the same behavior when using the tutorial dataset.

[apal6]

Hi @Paoloorder66,

I have the exact error:

Were you able to fix this?

Thank you so much!

[smorabit]

@apal6 @Paoloorder66

Are either of you able to reproduce this error with the tutorial data, or does this only appear on your own dataset?

[apal6]

Hi @smorabit, I wasn't able to reproduce with the tutorial data. It just works fine.

Looks like there is something with my data but not sure what as there isn't any error. However, I just looked at the warnings after running seurat_obj <- TestSoftPowers( seurat_obj, networkType = 'signed' # you can also use "unsigned" or "signed hybrid")

Warning messages: 1: In (function (x, y = NULL, robustX = TRUE, robustY = TRUE, ... : bicor: zero MAD in variable 'x'. Pearson correlation was used for individual columns with zero (or missing) MAD. 2: In (function (x, y = NULL, robustX = TRUE, robustY = TRUE, ... :

Any suggestions?

Thank you, Aastha

[smorabit]

If you are able to run it on the tutorial data without this issue, it seems that the issue likely is due to something about your particular dataset. Unfortunately I don't have any suggestions or any ability to diagnose the problem / provide a solution unless I can reproduce the behavior myself.

[smorabit]

Closing due to inactivity.

[yao50985098]

I got the same issue here, is there any solutions?

[smorabit]

Are you able to provide a reproducible example that I can run? I have not found this error myself so it is difficult for me to help at this time.

[ryan-gorzek]

I ran into this same issue. It turns out that I was confusing the tom_name parameter in ConstructNetwork (which can be whatever you wish) and the group_name parameter in ModuleConnectivity (which should be a set drawn from the column you specify in group.by). Because these parameters are both specified as 'INH' in the tutorial, I mixed them up. I hope this is helpful to others!