Modularity analysis using Dormann and Strauss, 2014 method

[Danvel91]

Hi!
I am conducting an ecological analysis of a metavirome using the computeModules function. I´ve been able to compute the modules and plot them, but I always get warning messages saying that the matrix length of the modules object and the original web are not same, and because of that I believe that not all nodes are displayed. I attach you my code and the warning messages:

otus.net <- graph.data.frame(links.net, nodes.net, directed = FALSE)

otus.net.adj <- get.adjacency(otus.net, sparse = FALSE, names = TRUE)
modules.net <- computeModules(otus.net.adj, deep = FALSE, tolerance = 1e-10)

plotModuleWeb(modules.net, plotModules = TRUE,
              rank = FALSE, weighted = FALSE, displayAlabels = TRUE,
              displayBlabels = TRUE, labsize = 1, xlabel = "", ylabel = "",
              square.border = "white", fromDepth = 0, upToDepth = -1)

I´ve used upToDepth = -1 with the idea of plotting all modules (If upToDepth is smaller
than fromDepth, all modules are plot)

Warning messages:
1: In dim(slot(moduleWebObject, "originalWeb")) == 0 || dim(slot(moduleWebObject, :
'length(x) = 2 > 1' in coercion to 'logical(1)'
2: In dim(slot(moduleWebObject, "originalWeb")) == 0 || dim(slot(moduleWebObject, :
'length(x) = 2 > 1' in coercion to 'logical(1)'
3: In dim(slot(moduleWebObject, "originalWeb")) == 0 || dim(slot(moduleWebObject, :
'length(x) = 2 > 1' in coercion to 'logical(1)'

Info about R session:

sessionInfo()
R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22621)

Matrix products: default

locale:
[1] LC_COLLATE=Spanish_Spain.utf8  LC_CTYPE=Spanish_Spain.utf8   
[3] LC_MONETARY=Spanish_Spain.utf8 LC_NUMERIC=C                  
[5] LC_TIME=Spanish_Spain.utf8    

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

other attached packages:
 [1] pheatmap_1.0.12      RColorBrewer_1.1-3   forcats_1.0.0       
 [4] stringr_1.5.0        dplyr_1.1.0          purrr_1.0.1         
 [7] readr_2.1.4          tidyr_1.3.0          tibble_3.1.8        
[10] tidyverse_1.3.2      readxl_1.4.2         dendextend_1.17.1   
[13] factoextra_1.0.7     ggplot2_3.4.1        cluster_2.1.4       
[16] igraph_1.4.0         relaimpo_2.2-6       mitools_2.4         
[19] survey_4.1-1         survival_3.5-0       Matrix_1.5-3        
[22] boot_1.3-28.1        MASS_7.3-58.2        bipartite_2.18      
[25] sna_2.7-1            network_1.18.1       statnet.common_4.8.0
[28] vegan_2.6-4          lattice_0.20-45      permute_0.9-7       

loaded via a namespace (and not attached):
 [1] viridis_0.6.2       httr_1.4.4          maps_3.4.1         
 [4] jsonlite_1.8.4      viridisLite_0.4.1   splines_4.2.2      
 [7] modelr_0.1.10       dotCall64_1.0-2     assertthat_0.2.1   
[10] googlesheets4_1.0.1 cellranger_1.1.0    ggrepel_0.9.3      
[13] pillar_1.8.1        backports_1.4.1     glue_1.6.2         
[16] rvest_1.0.3         colorspace_2.1-0    pkgconfig_2.0.3    
[19] broom_1.0.3         haven_2.5.1         corpcor_1.6.10     
[22] scales_1.2.1        tzdb_0.3.0          timechange_0.2.0   
[25] googledrive_2.0.0   mgcv_1.8-41         generics_0.1.3     
[28] ellipsis_0.3.2      withr_2.5.0         cli_3.6.0          
[31] crayon_1.5.2        magrittr_2.0.3      fs_1.6.1           
[34] fansi_1.0.4         nlme_3.1-162        xml2_1.3.3         
[37] tools_4.2.2         hms_1.1.2           gargle_1.3.0       
[40] lifecycle_1.0.3     reprex_2.0.2        munsell_0.5.0      
[43] compiler_4.2.2      rlang_1.0.6         rstudioapi_0.14    
[46] spam_2.9-1          gtable_0.3.1        DBI_1.1.3          
[49] R6_2.5.1            gridExtra_2.3       lubridate_1.9.2    
[52] utf8_1.2.3          stringi_1.7.12      parallel_4.2.2     
[55] Rcpp_1.0.10         fields_14.1         vctrs_0.5.2        
[58] dbplyr_2.3.0        tidyselect_1.2.0    coda_0.19-4 

Is this related with the window size or with the length of the matrix? Many thanks in advance for your support,

Best

[rubenroos]

Hi!

I'm getting a similar error when running plotModuleWeb follwing the example code for computeModules() (https://rdrr.io/cran/bipartite/man/computeModules.html) and similar issues when using the script and data provided by Marini et al. 2019 (https://besjournals.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2F1365-2664.13337&file=jpe13337-sup-0001-Supinfo.doc).

data(small1976)
(res <- computeModules(small1976)) 
plotModuleWeb(res)

Error in dim(slot(moduleWebObject, "originalWeb")) == 0 || dim(slot(moduleWebObject, :
'length = 2' in coercion to 'logical(1)'

Session info

R version 4.3.1 (2023-06-16 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)

Matrix products: default

locale:
[1] C

time zone: Europe/Oslo
tzcode source: internal

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

other attached packages:
 [1] visNetwork_2.1.2     igraph_1.5.1         bipartite_2.18       sna_2.7-1            network_1.18.1       statnet.common_4.9.0
 [7] vegan_2.6-4          lattice_0.21-8       permute_0.9-7        reshape_0.8.9       

loaded via a namespace (and not attached):
 [1] Matrix_1.5-4.1    jsonlite_1.8.7    compiler_4.3.1    maps_3.4.1        Rcpp_1.0.11       parallel_4.3.1    cluster_2.1.4     splines_4.3.1    
 [9] yaml_2.3.7        fastmap_1.1.1     coda_0.19-4       plyr_1.8.8        knitr_1.43        htmlwidgets_1.6.2 MASS_7.3-60       dotCall64_1.0-2  
[17] tibble_3.2.1      pillar_1.9.0      rlang_1.1.1       utf8_1.2.3        xfun_0.40         viridisLite_0.4.2 cli_3.6.1         magrittr_2.0.3   
[25] mgcv_1.8-42       digest_0.6.33     grid_4.3.1        spam_2.9-1        lifecycle_1.0.3   nlme_3.1-162      fields_15.2       vctrs_0.6.3      
[33] evaluate_0.21     glue_1.6.2        fansi_1.0.4       rmarkdown_2.24    ellipsis_0.3.2    tools_4.3.1       pkgconfig_2.0.3   htmltools_0.5.6

Many thanks for the support!
Best wishes

[cdormann]

Hm. So I think this issue is fixed with the 2.19 release. At least I cannot reproduce any of the errors, and it works "perfectly" with both the small1976 example and a larger memmott1999 data set (both in the default and the deep=T setting with method="DormannStrauss"). Please re-open issue if problem still exists! Reproducible example like that of rubenroos much appreciated!