Error when running mixedModelDE

Hi, Not sure if this is the proper channel to communicate issues. I have been following the vignette from bioconductor. I encountered a couple of hiccups that I was able to solve but I can't figure out why I am getting the following error with mixedModelDE (problem with env??) . I tried different ways to indicate the formula and using different factors but I get the same error. Bellow, I have the session info.

Any suggestions on how to solve it.

BTW, the link to the demo data in that pdf doesn't seem to work and the one that I found on your website doesn't have the same data structures to follow the vignette.

Thanks.

pData(target_Data)$testTEMP <- factor(pData(protocolData(target_Data))$CD8TEMP, c("HOT", "COLD"))
results <- c()
for(segment in c("pos","neg")) {
    ind <- pData(protocolData(target_Data))$segment == segment
    mixedOutmc <-
        mixedModelDE(target_Data[, ind],
                     elt = "log_q",
                     modelFormula = ~ testTEMP + 1,
                     groupVar = "testTEMP",
                     #nCores = parallel::detectCores(),
                     #multiCore = FALSE
                     )

    # format results as data.frame
    r_test <- do.call(rbind, mixedOutmc["lsmeans", ])
    tests <- rownames(r_test)
    r_test <- as.data.frame(r_test)
    r_test$Contrast <- tests

    # use lapply in case you have multiple levels of your test factor to
    # correctly associate gene name with it's row in the results table
    r_test$Gene <- 
        unlist(lapply(colnames(mixedOutmc),
                      rep, nrow(mixedOutmc["lsmeans", ][[1]])))
    r_test$Subset <- region
    r_test$FDR <- p.adjust(r_test$`Pr(>|t|)`, method = "fdr")
    r_test <- r_test[, c("Gene", "Subset", "Contrast", "Estimate", 
                         "Pr(>|t|)", "FDR")]
    results <- rbind(results, r_test)
}

Error in eval(predvars, data, env): object 'testTEMP' not found
Traceback:

1. mixedModelDE(target_Data[, ind], elt = "log_q", modelFormula = ~testTEMP + 
 .     1, groupVar = "testTEMP", )
2. assayDataApply(object, 1, deFunc, groupVar, pDat, formula(paste("expr", 
 .     as.character(modelFormula)[2], sep = " ~ ")), pairwise, elt = elt)
3. assayDataApply(object, 1, deFunc, groupVar, pDat, formula(paste("expr", 
 .     as.character(modelFormula)[2], sep = " ~ ")), pairwise, elt = elt)
4. .local(X, MARGIN, FUN, ...)
5. .apply(X = mat, MARGIN = MARGIN, FUN = FUN, ..., .df = df, .kvs = kvs)
6. FUN(X[i, ], ...)
7. suppressMessages(lmerTest::lmer(modelFormula, dat))
8. withCallingHandlers(expr, message = function(c) if (inherits(c, 
 .     classes)) tryInvokeRestart("muffleMessage"))
9. lmerTest::lmer(modelFormula, dat)
10. eval.parent(mc)
11. eval(expr, p)
12. eval(expr, p)
13. lme4::lmer(formula = modelFormula, data = dat)
14. eval(mc, parent.frame(1L))
15. eval(mc, parent.frame(1L))
16. lme4::lFormula(formula = modelFormula, data = dat, control = structure(list(
  .     optimizer = "nloptwrap", restart_edge = TRUE, boundary.tol = 1e-05, 
  .     calc.derivs = TRUE, use.last.params = FALSE, checkControl = list(
  .         check.nobs.vs.rankZ = "ignore", check.nobs.vs.nlev = "stop", 
  .         check.nlev.gtreq.5 = "ignore", check.nlev.gtr.1 = "stop", 
  .         check.nobs.vs.nRE = "stop", check.rankX = "message+drop.cols", 
  .         check.scaleX = "warning", check.formula.LHS = "stop"), 
  .     checkConv = list(check.conv.grad = list(action = "warning", 
  .         tol = 0.002, relTol = NULL), check.conv.singular = list(
  .         action = "message", tol = 1e-04), check.conv.hess = list(
  .         action = "warning", tol = 1e-06)), optCtrl = list()), class = c("lmerControl", 
  . "merControl")))
17. eval(mf, parent.frame())
18. eval(mf, parent.frame())
19. stats::model.frame(data = dat, drop.unused.levels = TRUE, formula = expr ~ 
  .     testTEMP + 1)
20. model.frame.default(data = dat, drop.unused.levels = TRUE, formula = expr ~ 
  .     testTEMP + 1)
21. eval(predvars, data, env)
22. eval(predvars, data, env)

Session info

R version 4.2.0 (2022-04-22)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux Server 7.9 (Maipo)

Matrix products: default
BLAS/LAPACK:/conda_envs/nanostring/lib/libopenblasp-r0.3.20.so

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

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

other attached packages:
 [1] ggrepel_0.9.1           pheatmap_1.0.12         Rtsne_0.16             
 [4] umap_0.2.8.0            cowplot_1.1.1           reshape2_1.4.4         
 [7] scales_1.2.0            ggforce_0.3.3           dplyr_1.0.9            
[10] knitr_1.39              GeoMxWorkflows_1.2.0    GeomxTools_3.0.1       
[13] NanoStringNCTools_1.4.0 ggplot2_3.3.6           S4Vectors_0.34.0       
[16] Biobase_2.56.0          BiocGenerics_0.42.0    

loaded via a namespace (and not attached):
 [1] nlme_3.1-158           bitops_1.0-7           EnvStats_2.7.0        
 [4] RColorBrewer_1.1-3     GenomeInfoDb_1.32.2    repr_1.1.4            
 [7] numDeriv_2016.8-1.1    tools_4.2.0            utf8_1.2.2            
[10] R6_2.5.1               vipor_0.4.5            rgeos_0.5-9           
[13] colorspace_2.0-3       withr_2.5.0            sp_1.5-0              
[16] tidyselect_1.1.2       GGally_2.1.2           compiler_4.2.0        
[19] progressr_0.10.1       cli_3.3.0              askpass_1.1           å
[22] pbdZMQ_0.3-7           systemfonts_1.0.4      stringr_1.4.0         
[25] digest_0.6.29          minqa_1.2.4            rmarkdown_2.14        
[28] XVector_0.36.0         base64enc_0.1-3        pkgconfig_2.0.3       
[31] htmltools_0.5.2        parallelly_1.32.0      lme4_1.1-29           
[34] fastmap_1.1.0          htmlwidgets_1.5.4      rlang_1.0.3           
[37] ggthemes_4.2.4         readxl_1.4.0           farver_2.1.0          
[40] generics_0.1.2         jsonlite_1.8.0         RCurl_1.98-1.7        
[43] magrittr_2.0.3         GenomeInfoDbData_1.2.8 Matrix_1.4-1          
[46] Rcpp_1.0.8.3           ggbeeswarm_0.6.0       IRkernel_1.3          
[49] munsell_0.5.0          fansi_1.0.3            reticulate_1.25       
[52] lifecycle_1.0.1        yaml_2.3.5             stringi_1.7.6         
[55] MASS_7.3-57            zlibbioc_1.42.0        plyr_1.8.7            
[58] grid_4.2.0             parallel_4.2.0         listenv_0.8.0         
[61] crayon_1.5.1           lattice_0.20-45        IRdisplay_1.1         
[64] Biostrings_2.64.0      splines_4.2.0          pillar_1.7.0          
[67] uuid_1.1-0             boot_1.3-28            rjson_0.2.21          
[70] future.apply_1.9.0     codetools_0.2-18       glue_1.6.2            
[73] ggiraph_0.8.2          evaluate_0.15          outliers_0.15         
[76] SeuratObject_4.1.0     BiocManager_1.30.18    data.table_1.14.2     
[79] png_0.1-7              tweenr_1.0.2           vctrs_0.4.1           
[82] nloptr_2.0.3           cellranger_1.1.0       openssl_2.0.2         
[85] polyclip_1.10-0        gtable_0.3.0           purrr_0.3.4           
[88] reshape_0.8.9          future_1.26.1          xfun_0.31             
[91] RSpectra_0.16-1        tibble_3.1.7           lmerTest_3.1-3        
[94] beeswarm_0.4.0         IRanges_2.30.0         globals_0.15.1        
[97] ellipsis_0.3.2         BiocStyle_2.24.0  
~~~

Nanostring-Biostats / GeomxTools

Error when running mixedModelDE #174

Session info