Error in netVisual_embeddingPairwise() - arguments imply differing number of rows

[cgoneill]

Hello, and thank you for an excellent package - I've gotten a lot of good use out of it so far.

I have a merged CellChat object built from four separate conditions that I'm trying to do comparative analysis on, but I'm running into an error when I run netVisual_embeddingPairwise(). I saw some discussion of this issue secondary to another in #174, but I didn't see an answer there.

> unwounded.cellchat %<>% computeNetSimilarityPairwise(type = "functional") %>% 
+   netEmbedding(type = "functional") %>% 
+   netClustering(type = "functional")
Compute signaling network similarity for datasets 1 2 3 4 
Manifold learning of the signaling networks for datasets 1 2 3 4 
Classification learning of the signaling networks for datasets 1 2 3 4 
> # visualize in 2D space
> (gg <- netVisual_embeddingPairwise(
+   unwounded.cellchat, type = "functional", label.size = 3.5
+ ))
2D visualization of signaling networks from datasets 1 2 3 4 
Error in data.frame(x = Y[, 1], y = Y[, 2], Commun.Prob. = prob_sum/max(prob_sum),  : 
  arguments imply differing number of rows: 241, 243

Examining the netP slot, I found the functional slot under netP had a matrix slot with 243 x 243, but the dr and group variables only had 241. I assume this disconnect between the matrix slot and the dr and group slots is where the problem stems from, but I'm not sure how to fix this. I ran the same workflow on the structural similarity, but did not encounter this issue there, nor did I encounter this issue working with the comparative analysis vignette.

> unwounded.cellchat %<>% computeNetSimilarityPairwise(type = "structural") %>% 
+   netEmbedding(type = "structural") %>% 
+   netClustering(type = "structural")
Compute signaling network similarity for datasets 1 2 3 4 
Manifold learning of the signaling networks for datasets 1 2 3 4 
Classification learning of the signaling networks for datasets 1 2 3 4 
> # visualize in 2D space
> (gg1 <- netVisual_embeddingPairwise(unwounded.cellchat, 
+                                     type = "structural", 
+                                     label.size = 3.5))
2D visualization of signaling networks from datasets 1 2 3 4

Here's the session info I'm working with:

> sessionInfo()
R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: /usr/local/intel/compilers_and_libraries_2020.2.254/linux/mkl/lib/intel64_lin/libmkl_rt.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8      
 [8] LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] BiocParallel_1.30.3         reticulate_1.25             ggalluvial_0.12.3           NMF_0.24.0                  cluster_2.1.3               rngtools_1.5.2             
 [7] pkgmaker_0.32.2             registry_0.5-1              patchwork_1.1.1             pheatmap_1.0.12             RColorBrewer_1.1-3          scater_1.24.0              
[13] scuttle_1.6.2               condiments_1.4.0            tradeSeq_1.10.0             slingshot_2.4.0             TrajectoryUtils_1.4.0       princurve_2.1.6            
[19] enrichplot_1.16.1           org.Mm.eg.db_3.15.0         AnnotationDbi_1.58.0        clusterProfiler_4.4.2       enrichR_3.0                 clustree_0.4.4             
[25] ggraph_2.0.5                scCustomize_0.7.0           Scillus_0.5.0               harmony_0.1.0               Rcpp_1.0.8.3                DoubletFinder_2.0.3        
[31] DropletUtils_1.16.0         SingleCellExperiment_1.18.0 SummarizedExperiment_1.26.1 GenomicRanges_1.48.0        GenomeInfoDb_1.32.2         IRanges_2.30.0             
[37] S4Vectors_0.34.0            MatrixGenerics_1.8.0        matrixStats_0.62.0          openxlsx_4.2.5              cowplot_1.1.1               magrittr_2.0.3             
[43] forcats_0.5.1               stringr_1.4.0               purrr_0.3.4                 readr_2.1.2                 tidyr_1.2.0                 tibble_3.1.7               
[49] tidyverse_1.3.1             Matrix_1.4-1                SoupX_1.6.1                 sp_1.5-0                    SeuratObject_4.1.0          Seurat_4.1.1               
[55] CellChat_1.4.0              synchronicity_1.3.5         bigmemory_4.6.1             Biobase_2.56.0              BiocGenerics_0.42.0         ggplot2_3.3.6              
[61] igraph_1.3.2                dplyr_1.0.9                

loaded via a namespace (and not attached):
  [1] Ecume_0.9.1               spatstat.linnet_2.3-2     graphlayouts_0.8.0        pbapply_1.5-0             lattice_0.20-45           haven_2.5.0               vctrs_0.4.1              
  [8] mgcv_1.8-40               blob_1.2.3                survival_3.3-1            prodlim_2019.11.13        spatstat.data_2.2-0       later_1.3.0               DBI_1.1.2                
 [15] R.utils_2.11.0            uwot_0.1.11               dqrng_0.3.0               zlibbioc_1.42.0           rgeos_0.5-9               htmlwidgets_1.5.4         GlobalOptions_0.1.2      
 [22] future_1.26.1             formattable_0.2.1         leiden_0.4.2              parallel_4.2.0            irlba_2.3.5               tidygraph_1.2.1           KernSmooth_2.23-20       
 [29] promises_1.2.0.1          DelayedArray_0.22.0       limma_3.52.1              magick_2.7.3              RSpectra_0.16-1           fs_1.5.2                  textshaping_0.3.6        
 [36] fastmatch_1.1-3           digest_0.6.29             png_0.1-7                 sctransform_0.3.3         scatterpie_0.1.7          DOSE_3.22.0               here_1.0.1               
 [43] pkgconfig_2.0.3           GO.db_3.15.0              dittoSeq_1.9.1            gridBase_0.4-7            spatstat.random_2.2-0     DelayedMatrixStats_1.18.0 gower_1.0.0              
 [50] ggbeeswarm_0.6.0          iterators_1.0.14          statnet.common_4.6.0      network_1.17.2            circlize_0.4.15           beeswarm_0.4.0            GetoptLong_1.0.5         
 [57] xfun_0.31                 zoo_1.8-10                tidyselect_1.1.2          reshape2_1.4.4            kernlab_0.9-30            ica_1.0-2                 viridisLite_0.4.0        
 [64] rlang_1.0.3               spatstat_2.3-4            glue_1.6.2                modelr_0.1.8              lava_1.6.10               colorway_0.2.0            ggsignif_0.6.3           
 [71] recipes_0.2.0             labeling_0.4.2            httpuv_1.6.5              class_7.3-20              BiocNeighbors_1.14.0      DO.db_2.9                 jsonlite_1.8.0           
 [78] XVector_0.36.0            bit_4.0.4                 mime_0.12                 systemfonts_1.0.4         gridExtra_2.3             stringi_1.7.6             spatstat.sparse_2.1-1    
 [85] scattermore_0.8           yulab.utils_0.0.4         hardhat_1.1.0             bitops_1.0-7              cli_3.3.0                 rhdf5filters_1.8.0        RSQLite_2.2.14           
 [92] bigmemory.sri_0.1.3       data.table_1.14.2         rstudioapi_0.13           nlme_3.1-157              qvalue_2.28.0             ggprism_1.0.3.9000        locfit_1.5-9.5           
 [99] janitor_2.1.0             listenv_0.8.0             miniUI_0.1.1.1            gridGraphics_0.5-1        R.oo_1.24.0               dbplyr_2.2.0              readxl_1.4.0             
[106] lifecycle_1.0.1           timeDate_3043.102         transport_0.12-2          distinct_1.8.0            munsell_0.5.0             cellranger_1.1.0          R.methodsS3_1.8.1        
[113] codetools_0.2-18          coda_0.19-4               vipor_0.4.5               lmtest_0.9-40             xtable_1.8-4              ROCR_1.0-11               abind_1.4-5              
[120] farver_2.1.0              FNN_1.1.3.1               parallelly_1.32.0         RANN_2.6.1                aplot_0.1.6               ggtree_3.4.0              RcppAnnoy_0.0.19         
[127] goftest_1.2-3             future.apply_1.9.0        tidytree_0.3.9            ellipsis_0.3.2            lubridate_1.8.0           ggridges_0.5.3            reprex_2.0.1             
[134] fgsea_1.22.0              paletteer_1.4.0           spatstat.utils_2.3-1      htmltools_0.5.2           utf8_1.2.2                plotly_4.10.0             ModelMetrics_1.2.2.2     
[141] e1071_1.7-11              ggpubr_0.4.0              withr_2.5.0               fitdistrplus_1.1-8        bit64_4.0.5               doRNG_1.8.2               foreach_1.5.2            
[148] Biostrings_2.64.0         spatstat.core_2.4-4       progressr_0.10.1          GOSemSim_2.22.0           ragg_1.2.2                rsvd_1.0.5                ScaledMatrix_1.4.0       
[155] memoise_2.0.1             evaluate_0.15             tzdb_0.3.0                caret_6.0-92              curl_4.3.2                fansi_1.0.3               tensor_1.5               
[162] edgeR_3.38.1              cachem_1.0.6              deldir_1.0-6              rjson_0.2.21              rstatix_0.7.0             ggrepel_0.9.1             clue_0.3-61              
[169] rprojroot_2.0.3           tools_4.2.0               RCurl_1.98-1.7            proxy_0.4-27              car_3.1-0                 ape_5.6-2                 ggplotify_0.1.0          
[176] xml2_1.3.3                httr_1.4.3                assertthat_0.2.1          rmarkdown_2.14            globals_0.15.1            R6_2.5.1                  Rhdf5lib_1.18.2          
[183] nnet_7.3-17               KEGGREST_1.36.0           treeio_1.20.0             shape_1.4.6               beachmat_2.12.0           rematch2_2.1.2            HDF5Array_1.24.1         
[190] sna_2.7                   BiocSingular_1.12.0       rhdf5_2.40.0              splines_4.2.0             snakecase_0.11.0          carData_3.0-5             ggfun_0.0.6              
[197] colorspace_2.0-3          generics_0.1.2            pillar_1.7.0              tweenr_1.0.2              uuid_1.1-0                GenomeInfoDbData_1.2.8    plyr_1.8.7               
[204] gtable_0.3.0              rvest_1.0.2               zip_2.2.0                 knitr_1.39                ComplexHeatmap_2.12.0     shadowtext_0.1.2          fastmap_1.1.0            
[211] Cairo_1.5-15              doParallel_1.0.17         broom_0.8.0               scales_1.2.0              backports_1.4.1           ipred_0.9-13              hms_1.1.1                
[218] ggforce_0.3.3             Rtsne_0.16                shiny_1.7.1               polyclip_1.10-0           grid_4.2.0                lazyeval_0.2.2            crayon_1.5.1             
[225] MASS_7.3-57               downloader_0.4            pROC_1.18.0               sparseMatrixStats_1.8.0   viridis_0.6.2             svglite_2.1.0             rpart_4.1.16             
[232] compiler_4.2.0            spatstat.geom_2.4-0

[cgoneill]

I realized it may be of use to provide the traceback() report, so here's that:

> traceback()
3: stop(gettextf("arguments imply differing number of rows: %s", 
       paste(unique(nrows), collapse = ", ")), domain = NA)
2: data.frame(x = Y[, 1], y = Y[, 2], Commun.Prob. = prob_sum/max(prob_sum), 
       labels = as.character(labels), clusters = as.factor(clusters), 
       group = factor(group, levels = unique(group)))
1: netVisual_embeddingPairwise(unwounded.cellchat, type = "functional", 
       label.size = 3.5)

[Matthew1309]

I am having the same issue

[siefejo1]

Same issue here as well

[sqjin]

@siefejo1 Can you share me a data that can replicate this error?

[siefejo1]

I can share it with you privately. What's the best way to reach you?

[sqjin]

@siefejo1 Either dropbox/google drive/OneDrive is fine. My gmail is [email protected]

[siefejo1]

Sorry, but apparently I am unable to provide the data. I did figure out the issue though. On line 26 of the netVisual_embeddingPairwise() function: pathway.remove <- sub("--.*", "", pathway.remove) removes the dataset annotation from the pathways, but then line 32: pathway.remove.idx <- which(paste0(dimnames(probi)[[3]],"--",object.names[i]) %in% pathway.remove) expects that format. Commenting out line 26 solved the problem for me

[wajm]

Same issue here as well

[wajm]

Is there any update regarding this issue?

netVisual_embeddingPairwise(cellchat, type = "functional", label.size = 3.5) 2D visualization of signaling networks from datasets 1 2 Error in data.frame(x = Y[, 1], y = Y[, 2], Commun.Prob. = prob_sum/max(prob_sum), : arguments imply differing number of rows: 76, 78 traceback() 3: stop(gettextf("arguments imply differing number of rows: %s", paste(unique(nrows), collapse = ", ")), domain = NA) 2: data.frame(x = Y[, 1], y = Y[, 2], Commun.Prob. = prob_sum/max(prob_sum), labels = as.character(labels), clusters = as.factor(clusters), group = factor(group, levels = unique(group))) 1: netVisual_embeddingPairwise(cellchat, type = "functional", label.size = 3.5)

[sqjin]

@wajm The error should be fixed now. please reinstall it .

[Rainjie-afk]

@wajm The error should be fixed now. please reinstall it .

Thanks for your great Packages, but I still got the same error even after installing Version 1.6.1. netVisual_embeddingPairwise() Error message : data.frame(x = Y[, 1], y = Y[, 2], Commun.Prob. = prob_sum/max(prob_sum)