Dear all,

I am running a code I wrote 1 year ago that worked perfectly. However, now it seems that the combineTwoExpressionSet function from a4Base is not working properly. It seems it does the job because the line is run with no errors, but when I try tu run the next line (quantileNorm function) it gives an error (see below). And I realize that the problem is that the combineTwoExpressionSet function is not combining properly the expression sets as there are no features in the combined Eset (see below) while there are in the separate Esets.

I will really appreciate if someone could provide some help on what could be happening and how to fix it!

Thank you!

GEO84<-getGEOSuppFiles("GSE84113")
GEO66<-getGEOSuppFiles("GSE66926") 

untar("GSE84113/GSE84113_RAW.tar", exdir = getwd())
untar("GSE66926/GSE66926_RAW.tar", exdir = getwd())

# reading cel files
GEOFS84 <- read.celfiles(filenames = c("GSM2227385_25374.CEL.gz","GSM2227386_25375.CEL.gz",
                                       "GSM2227387_25376.CEL.gz","GSM2227388_25377.CEL.gz","GSM2227389_25378.CEL.gz"))
GEOFS66 <- read.celfiles(filenames = c("GSM1634433_23164.CEL.gz", "GSM1634434_23165.CEL.gz"))

# renaming samples
sampleNames(GEOFS84)<-gsub("GSM2227","",sampleNames(GEOFS84))
sampleNames(GEOFS84)<-gsub(".CEL.gz","",sampleNames(GEOFS84))
sampleNames(GEOFS66)<-gsub("GSM16344","",sampleNames(GEOFS66))
sampleNames(GEOFS66)<-gsub(".CEL.gz","",sampleNames(GEOFS66))

# normalization
GEOFS84.rma<-rma(GEOFS84,target="core")
GEOFS66.rma<-rma(GEOFS66,target="core")

# problematic code with corresponding output 

# Sample combination and quantile normalization

GEOS_microglia<-combineTwoExpressionSet(GEOFS84.rma,GEOFS66.rma)
GEOS_microglia_quant = quantileNorm(GEOS_microglia)


> GEOS_microglia_quant = quantileNorm(GEOS_microglia)
Error in sort.int(x, na.last = na.last, decreasing = decreasing, ...) : 
  'x' must be atomic

> GEOS_microglia
ExpressionSet (storageMode: environment)
assayData: 0 features, 2 samples 
element names: exprs 
protocolData
rowNames: 385_25374 386_25375 ... 400_25389 (10 total)
varLabels: exprs dates
varMetadata: labelDescription channel
phenoData
rowNames: 385_25374 386_25375 ... 37_23168 (14 total)
varLabels: index
varMetadata: labelDescription channel
featureData: none
experimentData: use 'experimentData(object)'
Annotation: pd.mogene.1.0.st.v1

sessionInfo( )

R version 4.0.3 (2020-10-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

Matrix products: default

Random number generation:
  RNG:     Mersenne-Twister 
Normal:  Inversion 
Sample:  Rounding 

locale:
  [1] LC_COLLATE=Spanish_Spain.1252  LC_CTYPE=Spanish_Spain.1252    LC_MONETARY=Spanish_Spain.1252
[4] LC_NUMERIC=C                   LC_TIME=Spanish_Spain.1252    

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

other attached packages:
  [1] pd.mogene.1.0.st.v1_3.14.1           DBI_1.1.1                           
[3] RSQLite_2.2.1                        topGO_2.42.0                        
[5] SparseM_1.78                         GO.db_3.12.1                        
[7] graph_1.68.0                         sva_3.38.0                          
[9] BiocParallel_1.24.1                  genefilter_1.72.1                   
[11] mgcv_1.8-33                          nlme_3.1-151                        
[13] a4Base_1.38.0                        a4Core_1.38.0                       
[15] a4Preproc_1.38.0                     ReactomePA_1.34.0                   
[17] oligo_1.54.1                         Biostrings_2.58.0                   
[19] XVector_0.30.0                       oligoClasses_1.52.0                 
[21] ff_4.0.4                             bit_4.0.4                           
[23] mogene10sttranscriptcluster.db_8.7.0 org.Mm.eg.db_3.12.0                 
[25] annotate_1.68.0                      XML_3.99-0.5                        
[27] AnnotationDbi_1.52.0                 GEOquery_2.58.0                     
[29] rlang_0.4.10                         limma_3.46.0                        
[31] gplots_3.1.1                         scatterplot3d_0.3-41                
[33] affyQCReport_1.68.0                  lattice_0.20-41                     
[35] affyPLM_1.66.0                       preprocessCore_1.52.0               
[37] gcrma_2.62.0                         affy_1.68.0                         
[39] forcats_0.5.1                        stringr_1.4.0                       
[41] purrr_0.3.4                          readr_1.4.0                         
[43] tidyr_1.1.2                          tibble_3.0.4                        
[45] tidyverse_1.3.0                      data.table_1.13.4                   
[47] ggplot2_3.3.3                        calibrate_1.7.7                     
[49] MASS_7.3-53                          TimeSeriesExperiment_1.8.0          
[51] SummarizedExperiment_1.20.0          MatrixGenerics_1.2.1                
[53] matrixStats_0.58.0                   clusterProfiler_3.18.0              
[55] DOSE_3.16.0                          casper_2.24.2                       
[57] GenomicRanges_1.42.0                 GenomeInfoDb_1.26.2                 
[59] IRanges_2.24.0                       S4Vectors_0.28.0                    
[61] Biobase_2.50.0                       BiocGenerics_0.36.0                 
[63] dplyr_1.0.4                         

loaded via a namespace (and not attached):
  [1] rappdirs_0.3.3           rtracklayer_1.49.5       coda_0.19-4              bit64_4.0.5             
[5] knitr_1.31               DelayedArray_0.16.1      RCurl_1.98-1.2           generics_0.1.0          
[9] GenomicFeatures_1.42.1   cowplot_1.1.1            shadowtext_0.0.7         VGAM_1.1-5              
[13] proxy_0.4-24             chron_2.3-56             enrichplot_1.10.2        xml2_1.3.2              
[17] lubridate_1.7.9.2        assertthat_0.2.1         viridis_0.5.1            xfun_0.20               
[21] hms_1.0.0                progress_1.2.2           caTools_1.18.1           dbplyr_2.1.0            
[25] readxl_1.3.1             igraph_1.2.6             geneplotter_1.68.0       ellipsis_0.3.1          
[29] backports_1.2.0          permute_0.9-5            biomaRt_2.46.3           vctrs_0.3.5             
[33] cachem_1.0.1             withr_2.4.1              ggforce_0.3.2            checkmate_2.0.0         
[37] vegan_2.5-7              GenomicAlignments_1.26.0 prettyunits_1.1.1        cluster_2.1.0           
[41] crayon_1.4.1             glmnet_4.1               edgeR_3.32.1             pkgconfig_2.0.3         
[45] tweenr_1.0.1             lifecycle_1.0.0          downloader_0.4           affyio_1.60.0           
[49] BiocFileCache_1.14.0     modelr_0.1.8             cellranger_1.1.0         polyclip_1.10-0         
[53] Matrix_1.2-18            reprex_1.0.0             viridisLite_0.3.0        bitops_1.0-6            
[57] KernSmooth_2.23-18       blob_1.2.1               shape_1.4.5              simpleaffy_2.66.0       
[61] qvalue_2.22.0            reactome.db_1.74.0       scales_1.1.1             memoise_2.0.0           
[65] graphite_1.36.0          magrittr_2.0.1           plyr_1.8.6               zlibbioc_1.36.0         
[69] compiler_4.0.3           scatterpie_0.1.5         RColorBrewer_1.1-2       DESeq2_1.30.0           
[73] Rsamtools_2.6.0          cli_2.3.1                gaga_2.36.0              tidyselect_1.1.0        
[77] stringi_1.5.3            yaml_2.2.1               GOSemSim_2.16.1          askpass_1.1             
[81] locfit_1.5-9.4           ggrepel_0.9.1            grid_4.0.3               fastmatch_1.1-0         
[85] tools_4.0.3              rstudioapi_0.13          foreach_1.5.1            gridExtra_2.3           
[89] farver_2.0.3             ggraph_2.0.4             digest_0.6.27            rvcheck_0.1.8           
[93] BiocManager_1.30.10      proto_1.0.0              Rcpp_1.0.5               broom_0.7.5             
[97] httr_1.4.2               mpm_1.0-22               colorspace_2.0-0         rvest_0.3.6             
[101] fs_1.5.0                 splines_4.0.3            graphlayouts_0.7.1       multtest_2.46.0         
[105] EBarrays_2.54.0          annaffy_1.62.0           xtable_1.8-4             jsonlite_1.7.2          
[109] dynamicTreeCut_1.63-1    tidygraph_1.2.0          R6_2.5.0                 gsubfn_0.7              
[113] pillar_1.5.0             htmltools_0.5.1.1        affxparser_1.62.0        glue_1.4.2              
[117] fastmap_1.1.0            codetools_0.2-18         fgsea_1.16.0             sqldf_0.4-11            
[121] curl_4.3                 gtools_3.8.2             openssl_1.4.3            survival_3.2-7          
[125] munsell_0.5.0            DO.db_2.9                GenomeInfoDbData_1.2.4   iterators_1.0.13        
[129] haven_2.3.1              reshape2_1.4.4           gtable_0.3.0