Issue running DA analysis

[carl-coyle]

Hi there I am trying to run a DA analysis (method DA-GLMM). However when I run the analysis I receive the error as seen below. Not too sure whats going wrong.

Session Info
**R version 4.0.3 (2020-10-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS High Sierra 10.13.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

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

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

other attached packages:
[1] lme4_1.1-25 Matrix_1.2-18 diffcyt_1.10.0 cowplot_1.1.0 CATALYST_1.14.0 SingleCellExperiment_1.12.0
[7] SummarizedExperiment_1.20.0 Biobase_2.50.0 GenomicRanges_1.42.0 GenomeInfoDb_1.26.0 IRanges_2.24.0 S4Vectors_0.28.0
[13] BiocGenerics_0.36.0 MatrixGenerics_1.2.0 matrixStats_0.57.0 readxl_1.3.1 forcats_0.5.0 stringr_1.4.0
[19] dplyr_1.0.2 purrr_0.3.4 readr_1.4.0 tidyr_1.1.2 tibble_3.0.4 ggplot2_3.3.2
[25] tidyverse_1.3.0 CytoML_2.2.1 flowWorkspace_4.2.0 flowCore_2.2.0

loaded via a namespace (and not attached):
[1] backports_1.2.0 circlize_0.4.11 drc_3.0-1 plyr_1.8.6 igraph_1.2.6 ConsensusClusterPlus_1.54.0
[7] splines_4.0.3 BiocParallel_1.24.1 scater_1.18.3 TH.data_1.0-10 digest_0.6.27 viridis_0.5.1
[13] fansi_0.4.1 magrittr_1.5 cluster_2.1.0 limma_3.46.0 aws.signature_0.6.0 openxlsx_4.2.3
[19] ComplexHeatmap_2.6.2 modelr_0.1.8 RcppParallel_5.0.2 sandwich_3.0-0 cytolib_2.2.0 jpeg_0.1-8.1
[25] colorspace_2.0-0 rvest_0.3.6 ggrepel_0.8.2 haven_2.3.1 xfun_0.19 crayon_1.3.4
[31] RCurl_1.98-1.2 jsonlite_1.7.1 hexbin_1.28.1 graph_1.68.0 survival_3.2-7 zoo_1.8-8
[37] glue_1.4.2 gtable_0.3.0 nnls_1.4 zlibbioc_1.36.0 XVector_0.30.0 GetoptLong_1.0.4
[43] DelayedArray_0.16.0 ggcyto_1.18.0 BiocSingular_1.6.0 car_3.0-10 Rgraphviz_2.34.0 shape_1.4.5
[49] abind_1.4-5 scales_1.1.1 mvtnorm_1.1-1 edgeR_3.32.0 DBI_1.1.0 Rcpp_1.0.5
[55] plotrix_3.7-8 viridisLite_0.3.0 clue_0.3-57 rsvd_1.0.3 foreign_0.8-80 FlowSOM_1.22.0
[61] tsne_0.1-3 httr_1.4.2 RColorBrewer_1.1-2 ellipsis_0.3.1 farver_2.0.3 pkgconfig_2.0.3
[67] XML_3.99-0.5 scuttle_1.0.0 uwot_0.1.9 dbplyr_2.0.0 locfit_1.5-9.4 labeling_0.4.2
[73] tidyselect_1.1.0 rlang_0.4.8 reshape2_1.4.4 munsell_0.5.0 cellranger_1.1.0 tools_4.0.3
[79] cli_2.1.0 generics_0.1.0 broom_0.7.2 ggridges_0.5.2 aws.s3_0.3.21 yaml_2.2.1
[85] knitr_1.30 fs_1.5.0 zip_2.1.1 nlme_3.1-150 RBGL_1.66.0 sparseMatrixStats_1.2.0
[91] xml2_1.3.2 compiler_4.0.3 rstudioapi_0.13 beeswarm_0.2.3 curl_4.3 png_0.1-7
[97] reprex_0.3.0 statmod_1.4.35 stringi_1.5.3 RSpectra_0.16-0 lattice_0.20-41 nloptr_1.2.2.2
[103] vctrs_0.3.4 pillar_1.4.6 lifecycle_0.2.0 BiocManager_1.30.10 GlobalOptions_0.1.2 RcppAnnoy_0.0.17
[109] BiocNeighbors_1.8.1 irlba_2.3.3 data.table_1.13.2 bitops_1.0-6 R6_2.5.0 latticeExtra_0.6-29
[115] gridExtra_2.3 RProtoBufLib_2.2.0 rio_0.5.16 vipor_0.4.5 codetools_0.2-18 boot_1.3-25
[121] MASS_7.3-53 gtools_3.8.2 assertthat_0.2.1 rjson_0.2.20 withr_2.3.0 multcomp_1.4-15
[127] GenomeInfoDbData_1.2.4 hms_0.5.3 ncdfFlow_2.36.0 grid_4.0.3 beachmat_2.6.1 minqa_1.2.4
[133] DelayedMatrixStats_1.12.0 carData_3.0-4 Cairo_1.5-12.2 Rtsne_0.15 lubridate_1.7.9.2 base64enc_0.1-3
[139] ggbeeswarm_0.6.0**

[markrobinsonuzh]

Dear @carl-coyle,

Could you give a few more details on the objects you are sending to diffcyt()? e.g., what is your experimental setup? What contrasts are specified?

My guess is that your model is over-parameterized, but it's hard to say without more details.

Cheers, Mark