ANCOMBC
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FrederickHuangLin
Contrasts error with lmerTest, but when run on individual ASVs the lmerTest works
Hello,
I'm trying to run ANCOMBC2 with repeated measures and am getting an error that I need help fixing.
Here is the code I'm running;
output = ancombc2(data = physeq, tax_level = "Genus",
fix_formula = "Term + Week",
rand_formula = "(Week | MouseID)",
p_adj_method = "holm", pseudo_sens = TRUE,
prv_cut = 0.10, lib_cut = 1000, s0_perc = 0.05,
group = "Term",
struc_zero = TRUE, neg_lb = TRUE,
alpha = 0.05, n_cl = 2, verbose = TRUE,
global = TRUE, pairwise = TRUE, dunnet = TRUE, trend = TRUE,
iter_control = list(tol = 1e-2, max_iter = 20,
verbose = TRUE),
em_control = list(tol = 1e-5, max_iter = 100),
lme_control = lme4::lmerControl(),
mdfdr_control = list(fwer_ctrl_method = "holm", B = 100),
trend_control = list(contrast = list(matrix(c(1, 0, -1, 1),
nrow = 2,
byrow = TRUE)),
node = list(2),
solver = "ECOS",
B = 8)
)
And the error:
Obtaining initial estimates ...
Error: Encountering the error for `lmerTest` package.
Please try to select one of your taxa and use its raw counts to fix the same linear mixed-effects model using `lmerTest` without the `ANCOMBC` package.
Load all necessary packages EXCEPT `ANCOMBC`, and see if the error arises due to package incompatibility or other issues.
The error message from `lmerTest` is as follows:
contrasts can be applied only to factors with 2 or more levels
In addition: Warning message:
The group variable has < 3 categories
The multi-group comparisons (global/pairwise/dunnet/trend) will be deactivated
My factor has two levels and when I follow the directions and run the lmerTest on individual taxa's raw counts I'm able to get output. Here is my run on two different ASVs:
detach("package:ANCOMBC", unload = TRUE)
lmer(ASV1 ~ Term + Week + (Week | MouseID), data_for_lmer)
Linear mixed model fit by REML ['lmerModLmerTest']
Formula: ASV1 ~ Term + Week + (Week | MouseID)
Data: data_for_lmer
REML criterion at convergence: 926.1512
Random effects:
Groups Name Std.Dev. Corr
MouseID (Intercept) 4.017
Week 1.445 -0.98
Residual 2.916
Number of obs: 177, groups: MouseID, 59
Fixed Effects:
(Intercept) TermFullterm Week
0.2844 1.3294 -0.1271
lmer(ASV2 ~ Term + Week + (Week | MouseID), data_for_lmer)
boundary (singular) fit: see help('isSingular')
Linear mixed model fit by REML ['lmerModLmerTest']
Formula: ASV2 ~ Term + Week + (Week | MouseID)
Data: data_for_lmer
REML criterion at convergence: -54.0103
Random effects:
Groups Name Std.Dev. Corr
MouseID (Intercept) 0.5870
Week 0.2203 -1.00
Residual 0.1367
Number of obs: 177, groups: MouseID, 59
Fixed Effects:
(Intercept) TermFullterm Week
0.108372 0.009403 -0.042373
optimizer (nloptwrap) convergence code: 0 (OK) ; 0 optimizer warnings; 1 lme4 warnings
Any help identifying what the issue could be and how to fix it would be greatly appreciated! Thank you, Samantha
> sessionInfo()
R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8 LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
time zone: America/New_York
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] DT_0.34.0 lmerTest_3.1-3 lme4_1.1-36 Matrix_1.7-0 tibble_3.2.1 dplyr_1.1.4
[7] ggplot2_3.5.1 qiime2R_0.99.6 phyloseq_1.48.0
loaded via a namespace (and not attached):
[1] fs_1.6.4 matrixStats_1.3.0
[3] bitops_1.0-7 DirichletMultinomial_1.46.0
[5] devtools_2.4.5 httr_1.4.7
[7] doParallel_1.0.17 numDeriv_2016.8-1.1
[9] profvis_0.3.8 tools_4.4.1
[11] doRNG_1.8.6.2 backports_1.5.0
[13] utf8_1.2.4 R6_2.5.1
[15] vegan_2.6-6.1 lazyeval_0.2.2
[17] mgcv_1.9-1 rhdf5filters_1.16.0
[19] permute_0.9-7 urlchecker_1.0.1
[21] withr_3.0.1 gridExtra_2.3
[23] cli_3.6.3 Biobase_2.64.0
[25] sandwich_3.1-1 sass_0.4.9
[27] mvtnorm_1.2-5 readr_2.1.5
[29] proxy_0.4-27 yulab.utils_0.1.8
[31] foreign_0.8-87 scater_1.32.0
[33] decontam_1.24.0 sessioninfo_1.2.2
[35] readxl_1.4.3 rstudioapi_0.16.0
[37] generics_0.1.3 crosstalk_1.2.1
[39] gtools_3.9.5 biomformat_1.30.0
[41] ggbeeswarm_0.7.2 fansi_1.0.6
[43] DescTools_0.99.60 S4Vectors_0.42.1
[45] DECIPHER_3.0.0 abind_1.4-5
[47] lifecycle_1.0.4 multcomp_1.4-28
[49] yaml_2.3.9 SummarizedExperiment_1.34.0
[51] gplots_3.1.3.1 rhdf5_2.48.0
[53] SparseArray_1.4.8 grid_4.4.1
[55] promises_1.3.0 crayon_1.5.3
[57] miniUI_0.1.1.1 lattice_0.22-6
[59] haven_2.5.4 beachmat_2.20.0
[61] pillar_1.9.0 knitr_1.48
[63] GenomicRanges_1.56.1 boot_1.3-30
[65] gld_2.6.8 codetools_0.2-20
[67] glue_1.7.0 data.table_1.15.4
[69] remotes_2.5.0 MultiAssayExperiment_1.30.3
[71] vctrs_0.6.5 treeio_1.26.0
[73] Rdpack_2.6.2 cellranger_1.1.0
[75] gtable_0.3.5 cachem_1.1.0
[77] xfun_0.45 rbibutils_2.3
[79] S4Arrays_1.4.1 mime_0.12
[81] reformulas_0.4.0 survival_3.6-4
[83] SingleCellExperiment_1.26.0 iterators_1.0.14
[85] bluster_1.14.0 gmp_0.7-5
[87] TH.data_1.1-4 ellipsis_0.3.2
[89] nlme_3.1-164 usethis_2.2.3
[91] bit64_4.0.5 GenomeInfoDb_1.40.1
[93] bslib_0.7.0 irlba_2.3.5.1
[95] vipor_0.4.7 KernSmooth_2.23-24
[97] rpart_4.1.23 DBI_1.2.3
[99] colorspace_2.1-0 BiocGenerics_0.50.0
[101] Hmisc_5.2-0 nnet_7.3-19
[103] ade4_1.7-22 NADA_1.6-1.1
[105] Exact_3.3 tidyselect_1.2.1
[107] bit_4.0.5 compiler_4.4.1
[109] htmlTable_2.4.2 BiocNeighbors_1.22.0
[111] expm_1.0-0 DelayedArray_0.30.1
[113] checkmate_2.3.1 scales_1.3.0
[115] caTools_1.18.2 stringr_1.5.1
[117] digest_0.6.36 minqa_1.2.7
[119] rmarkdown_2.27 XVector_0.44.0
[121] htmltools_0.5.8.1 pkgconfig_2.0.3
[123] base64enc_0.1-3 sparseMatrixStats_1.16.0
[125] MatrixGenerics_1.16.0 fastmap_1.2.0
[127] rlang_1.1.4 htmlwidgets_1.6.4
[129] UCSC.utils_1.0.0 shiny_1.8.1.1
[131] zCompositions_1.5.0-4 DelayedMatrixStats_1.26.0
[133] jquerylib_0.1.4 zoo_1.8-12
[135] jsonlite_1.8.8 energy_1.7-12
[137] BiocParallel_1.38.0 BiocSingular_1.20.0
[139] magrittr_2.0.3 Formula_1.2-5
[141] scuttle_1.14.0 GenomeInfoDbData_1.2.12
[143] Rhdf5lib_1.26.0 munsell_0.5.1
[145] Rcpp_1.0.12 viridis_0.6.5
[147] ape_5.8 CVXR_1.0-15
[149] stringi_1.8.4 rootSolve_1.8.2.4
[151] zlibbioc_1.50.0 MASS_7.3-60.2
[153] plyr_1.8.9 pkgbuild_1.4.4
[155] parallel_4.4.1 ggrepel_0.9.5
[157] forcats_1.0.0 lmom_3.2
[159] Biostrings_2.72.1 splines_4.4.1
[161] multtest_2.60.0 hms_1.1.3
[163] igraph_2.0.3 rngtools_1.5.2
[165] reshape2_1.4.4 stats4_4.4.1
[167] ScaledMatrix_1.12.0 pkgload_1.4.0
[169] evaluate_0.24.0 BiocManager_1.30.23
[171] nloptr_2.1.1 tzdb_0.4.0
[173] foreach_1.5.2 httpuv_1.6.15
[175] tidyr_1.3.1 purrr_1.0.4
[177] rsvd_1.0.5 xtable_1.8-4
[179] Rmpfr_1.1-1 e1071_1.7-14
[181] tidytree_0.4.6 later_1.3.2
[183] viridisLite_0.4.2 class_7.3-22
[185] gsl_2.1-8 truncnorm_1.0-9
[187] memoise_2.0.1 beeswarm_0.4.0
[189] IRanges_2.38.0 cluster_2.1.6
[191] TreeSummarizedExperiment_2.12.0 mia_1.12.0
