`MicrobiomeStat::generate_beta_test_single` represents errors

[HuaZou]

Hello, when I ran the One-Click Reports Generation by using mStat_generate_report_single, it showed the error information.

in `colnames<-`:
! attempt to set 'colnames' on an object with less than two dimensions
Backtrace:
 1. MicrobiomeStat::generate_beta_test_single(...)
 2. GUniFrac::PermanovaG2(formula, data = data.obj$meta.dat)
 3. GUniFrac::adonis3(as.formula(paste("Y", "~", rhs)), data, ...)
 4. base::`colnames<-`(`*tmp*`, value = colnames(lhs))
                                                                                                                                                                                      
Error in `colnames<-`(`*tmp*`, value = colnames(lhs)) :

after debuging the code, the error actually was from GUniFrac::adonis3. I have no idea on how to solve it. Could you please give me some help?

The following codes were that I ran

data(peerj32.obj)

data.obj = peerj32.obj

# Specify variable names
group.var = "group" # Variable used for grouping samples, primary variable of interest
vis.adj.vars = c("sex") # Covariates whose effects need to be removed before visualization
test.adj.vars = c("sex") # Covariates whose effects need to be adjusted in statistical tests
subject.var = "subject" # Variable used for subject identification
time.var = "time" # Variable used for time points

# Specify diversity indices
alpha.name = c("shannon", "observed_species") # Alpha diversity indices to calculate
dist.name = c("BC",'Jaccard') # Beta diversity indices to calculate

# Specify feature levels for visualization and testing
vis.feature.level = c("Phylum", "Family", "Genus") # Feature levels for visualization to have an overview of the data
test.feature.level = "Family" # Feature level to use for testing

# Specify other parameters
feature.dat.type = "count" # Type of the feature data
theme.choice = "bw" # Theme choice for the plots
base.size = 20 # Base size for the plots

# Parameters for multiple testing. Following setting is just for illustration. In real data analysis, multiple testing correction should always be applied.  
feature.mt.method = "none" # Multiple testing method for differential feature analysis
feature.sig.level = 0.2 # Significance level cutoff for highlighting differential features 

# Specify output file
output.file = "mStat_generate_report_single_example.pdf" # Replace with your own file path for the output report

# Specify optional parameters
dist.obj = NULL # Replace with a pre-computed distance matrix if available
alpha.obj = NULL # Replace with a pre-computed alpha diversity matrix if available
depth = NULL # Replace with a desired rarefaction depth, if NULL, minimum depth will be used
t.level = "1" # Replace with a desired time level if time points have multiple levels
feature.box.axis.transform = "sqrt" # Axis transformation for feature boxplots
strata.var = "sex" # Variable to stratify on in visualization

# Specify parameters for feature retention
bar.area.feature.no = 20 # Number of top abundant features to retain in barplot and areaplot
heatmap.feature.no = 20 # Number of top abundant features to retain in heatmap
dotplot.feature.no = 40 # Number of top abundant features to retain in dotplot

# Run the function
mStat_generate_report_single(
   data.obj = data.obj,
   dist.obj = dist.obj,
   alpha.obj = alpha.obj,
   group.var = group.var,
   vis.adj.vars = vis.adj.vars,
   test.adj.vars = test.adj.vars,
   subject.var = subject.var,
   time.var = time.var,
   alpha.name = alpha.name,
   depth = depth,
   dist.name = dist.name,
   t.level = t.level,
   feature.box.axis.transform = feature.box.axis.transform,
   strata.var = strata.var,
   vis.feature.level = vis.feature.level,
   test.feature.level = test.feature.level,
   feature.dat.type = feature.dat.type,
   bar.area.feature.no = bar.area.feature.no,
   heatmap.feature.no = heatmap.feature.no,
   dotplot.feature.no = dotplot.feature.no,
   feature.mt.method = feature.mt.method,
   feature.sig.level = feature.sig.level,
   theme.choice = theme.choice,
   base.size = base.size,
   output.file = output.file
 )

My Environment Information

R version 4.3.3 (2024-02-29)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Sonoma 14.2

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-arm64/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: Asia/Shanghai
tzcode source: internal

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

other attached packages:
 [1] lubridate_1.9.3      forcats_1.0.0        stringr_1.5.1        dplyr_1.1.4          purrr_1.0.2          readr_2.1.5         
 [7] tidyr_1.3.1          ggplot2_3.5.1        tidyverse_2.0.0      MicrobiomeStat_1.1.3 tibble_3.2.1         rlang_1.1.3         

loaded via a namespace (and not attached):
 [1] utf8_1.2.4          generics_0.1.3      stringi_1.8.3       lattice_0.22-6      hms_1.1.3           statip_0.2.3       
 [7] lme4_1.1-35.1       magrittr_2.0.3      timechange_0.3.0    grid_4.3.3          iterators_1.0.14    foreach_1.5.2      
[13] Matrix_1.6-5        modeest_2.4.0       fansi_1.0.6         scales_1.3.0        stabledist_0.7-1    codetools_0.2-19   
[19] numDeriv_2016.8-1.1 cli_3.6.2           timeSeries_4032.109 munsell_0.5.0       splines_4.3.3       withr_3.0.0        
[25] tools_4.3.3         rmutil_1.1.10       parallel_4.3.3      tzdb_0.4.0          nloptr_2.0.3        stable_1.1.6       
[31] minqa_1.2.6         colorspace_2.1-0    boot_1.3-30         rpart_4.1.23        vctrs_0.6.5         R6_2.5.1           
[37] matrixStats_1.2.0   lifecycle_1.0.4     clue_0.3-65         MASS_7.3-60.0.1     cluster_2.1.6       pkgconfig_2.0.3    
[43] pillar_1.9.0        lmerTest_3.1-3      gtable_0.3.4        glue_1.7.0          Rcpp_1.0.12         xfun_0.43          
[49] tidyselect_1.2.1    rstudioapi_0.16.0   knitr_1.45          spatial_7.3-17      nlme_3.1-164        fBasics_4032.96    
[55] timeDate_4032.109   compiler_4.3.3