Hi,
I've encountered a rather peculiar software issue involving the phyloseq package and the lme4 package when analyzing longitudinal microbiome data. Below, please find a reproducible example that triggers the error:
First, when I run the mixed effects model code provided by lme4, it works perfectly:
data("sleepstudy", package = "lme4")
m <- lme4::lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
m
Linear mixed model fit by REML ['lmerModLmerTest']
Formula: Reaction ~ Days + (Days | Subject)
Data: sleepstudy
REML criterion at convergence: 1743.628
Random effects:
Groups Name Std.Dev. Corr
Subject (Intercept) 24.741
Days 5.922 0.07
Residual 25.592
Number of obs: 180, groups: Subject, 18
Fixed Effects:
(Intercept) Days
251.41 10.47
The above code runs without issues. However, when I load the phyloseq package and then attempt to run the same lme4 code, it results in errors:
library(phyloseq)
m <- lme4::lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
Error in t(do.call(sparseMatrix, do.call(rbind, lapply(seq_along(blist), :
invalid 'lazy' to R_sparse_transpose()
Even detaching the phyloseq package doesn't resolve the issue and leads to a different error message:
detach("package:phyloseq", unload = TRUE)
m <- lme4::lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
Error in t.default(do.call(sparseMatrix, do.call(rbind, lapply(seq_along(blist), :
argument is not a matrix
As of now, the only solution I've found is to restart the R session. Below is my sessionInfo():
version 4.3.1 (2023-06-16)
Platform: x86_64-apple-darwin20 (64-bit)
Running under: macOS Ventura 13.4.1
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: America/New_York
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] gtable_0.3.4 ggplot2_3.4.3 rhdf5_2.44.0 Biobase_2.60.0 lattice_0.21-8
[6] rhdf5filters_1.12.1 vctrs_0.6.3 tools_4.3.1 bitops_1.0-7 generics_0.1.3
[11] biomformat_1.28.0 stats4_4.3.1 parallel_4.3.1 tibble_3.2.1 fansi_1.0.4
[16] cluster_2.1.4 pkgconfig_2.0.3 Matrix_1.6-1 data.table_1.14.8 S4Vectors_0.38.1
[21] lifecycle_1.0.3 GenomeInfoDbData_1.2.10 compiler_4.3.1 stringr_1.5.0 Biostrings_2.68.1
[26] munsell_0.5.0 codetools_0.2-19 permute_0.9-7 GenomeInfoDb_1.36.3 RCurl_1.98-1.12
[31] pillar_1.9.0 nloptr_2.0.3 crayon_1.5.2 MASS_7.3-60 vegan_2.6-4
[36] iterators_1.0.14 boot_1.3-28.1 foreach_1.5.2 nlme_3.1-163 tidyselect_1.2.0
[41] digest_0.6.33 stringi_1.7.12 dplyr_1.1.3 reshape2_1.4.4 splines_4.3.1
[46] ade4_1.7-22 grid_4.3.1 colorspace_2.1-0 cli_3.6.1 magrittr_2.0.3
[51] survival_3.5-7 utf8_1.2.3 ape_5.7-1 scales_1.2.1 XVector_0.40.0
[56] igraph_1.5.1 multtest_2.56.0 lme4_1.1-34 IRanges_2.34.1 mgcv_1.9-0
[61] rlang_1.1.1 Rcpp_1.0.11 glue_1.6.2 BiocGenerics_0.46.0 rstudioapi_0.15.0
[66] minqa_1.2.6 jsonlite_1.8.7 R6_2.5.1 Rhdf5lib_1.22.1 plyr_1.8.8
[71] zlibbioc_1.46.0
Also, I using Bioconductor 3.17.
Any insights or advice on resolving this issue would be greatly appreciated.
Best regards,
Huang
