I have an expressionset with timepoints on one axis and different samples on the other axis.

I need to average the data for different samples which are currently defined as different "rowNames", the metadata for those samples is defined by varLabels: Cell.Type Cell.Number Compound.Name. I would like to average all the samples with the same Compound name at each time point, this would essentially create a new expression set with fewer samples.

What would be the best way to approach this?

Here is my expression set info:

ExpressionSet (storageMode: lockedEnvironment)
assayData: 2384 features, 39 samples 
  element names: exprs 
protocolData: none
phenoData
  rowNames: A1 A2 ... NA.3 (39 total)
  varLabels: Cell.Type Cell.Number Compound.Name
  varMetadata: X.labelDescription...c..Cell.Type....Cell.Number....Compound.Name... labelDescription
featureData
  featureNames: 0 0.006944444 ... 72.5775 (2384 total)
  fvarLabels: timepoints
  fvarMetadata: labelDescription
experimentData: use 'experimentData(object)'
Annotation:

sessionInfo( )
R version 4.0.2 (2020-06-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.4

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_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
 [1] readxl_1.3.1        forcats_0.5.0       stringr_1.4.0       dplyr_1.0.2         purrr_0.3.4        
 [6] readr_1.4.0         tidyr_1.1.2         tibble_3.0.4        ggplot2_3.3.2       tidyverse_1.3.0    
[11] RTCA_1.42.0         gtools_3.8.2        RColorBrewer_1.1-2  Biobase_2.50.0      BiocGenerics_0.36.0

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.5        cellranger_1.1.0  pillar_1.4.7      compiler_4.0.2    dbplyr_2.0.0      tools_4.0.2      
 [7] lubridate_1.7.9.2 jsonlite_1.7.1    lifecycle_0.2.0   gtable_0.3.0      pkgconfig_2.0.3   rlang_0.4.9      
[13] reprex_0.3.0      cli_2.2.0         DBI_1.1.0         rstudioapi_0.13   haven_2.3.1       withr_2.3.0      
[19] xml2_1.3.2        httr_1.4.2        fs_1.5.0          generics_0.1.0    vctrs_0.3.5       hms_0.5.3        
[25] grid_4.0.2        tidyselect_1.1.0  glue_1.4.2        R6_2.5.0          fansi_0.4.1       modelr_0.1.8     
[31] magrittr_2.0.1    backports_1.2.0   scales_1.1.1      ellipsis_0.3.1    rvest_0.3.6       assertthat_0.2.1 
[37] colorspace_2.0-0  utf8_1.1.4        stringi_1.5.3     munsell_0.5.0     broom_0.7.2       crayon_1.3.4

The easiest way to do that would be to use the avereps function from the limma package.