Hi! I'm following this guide to analyze the raw data from this study (https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-18670/).

I arrived at the "11.4 Adding more annotation" part, and tried running:

> anncols <- aaf.handler()[c(1:2,9:12)]
> atab <- aafTableAnn(T2$sym, "hgu133plus2.db", anncols)
Error in .checkKeysAreWellFormed(keys) : 
  keys must be supplied in a character vector with no NAs

So I removed the NA annotated probes with:

> T3 <- T2[complete.cases(T2[ , 2:3]), ]

And then:

> atab <- aafTableAnn(T3$sym, "hgu133plus2.db", anncols)
Error in .checkKeysAreWellFormed(keys) : 
  keys must be supplied in a character vector with no NAs

> T3$sym
  [1] NTPCR      LSM5       FAM122A    RSAD1     
  [5] NAA35      CDCA7L     C12orf29   UFM1      
  [9] NADK       CFAP20     SH2D1B     SLC30A5   
 [13] DIPK1A     PYROXD1    PPP6C      ARMC1     
 [17] FAM220A    VPS33B     CD3G       ATG5      
 [21] ZBED4      LANCL1     RLIM       ELAC1     
 [25] SRRD       GMEB1      ASH1L-AS1  LBH       
 [29] PIK3R4     ZXDB       FGFBP2     CCND2     
 [33] HSPA13     RPRD1B     CHORDC1    TMEM260   
 [37] GUF1       RTL6       DIPK1A     CA5BP1    
 [41] AASDH      RBM8A      RBM15B     RP9       
 [45] MAP3K1     ERVH-6     TMPO       USP1      
 [49] ABCC4      HIBADH     EEF1AKNMT  ZNF318    
 [53] DDX11L2    MAN1A2     ZNF449     LYRM7     
 [57] KLHL24     INIP       LRRC40     PUS3      
 [61] SLC38A1    ADGRG5     CCND2      ARIH2     
 [65] TMX1       SLC25A36   SMAD7      ING3      
 [69] CLPX       EMSY       CDC40      MTO1      
 [73] RNF125     MIA3       ADRB1      PDCD4-AS1 
 [77] SRP72      N4BP2L2    ASPHD2     RFC3      
 [81] JCHAIN     GOSR2      KLRF1      MAGED1    
 [85] CDK9       SIKE1      PET117     RBM25     
 [89] JAZF1      PDGFD      MTF2       TCFL5     
 [93] PLPBP      HACE1      CEP120     DNAJB14   
 [97] CDC73      TMEM185B   TENT4B     TMEM135   
[101] TNRC6C-AS1 GABPB2     SFMBT1     PRMT5     
[105] HOPX       MTO1       LACTB      CYP4V2    
[109] PCM1       TDP1       DYRK2      SART3     
[113] SEPT6      PLEKHG2    DCLRE1C    MTO1      
[117] MXRA7      ZFP90      SNX4       PDSS2     
[121] MTCH2      RORA       RBM7       GORASP2   
[125] SNRPA1     MOSPD1     TRIM14     PAICS     
[129] IFT122     TESK2      SHQ1       FBXL12    
[133] TMEM161B   CNIH1      TMEM33     KIAA0232  
[137] ANAPC16    VPS33B     RAD17      ALDH5A1   
[141] TRAPPC11   FBXO21     FLT3LG     BRD3OS    
[145] ATG2B      MFN1       UBLCP1     CD247     
[149] CD2        GSR        UEVLD      SYNE2     
[153] FBXO4      KPNA1      LOC285819  STRN      
[157] TUBGCP3    PEX13      ABHD15     METTL4    
[161] UHMK1      SEPHS1     ZNF550     OSBPL5    
[165] ATP6V1E2   SLCO4C1    EFL1       ADPRM     
[169] DHX36      ZNF322     GZMA       GNLY      
[173] HACD2     
168 Levels: AASDH ABCC4 ABHD15 ADGRG5 ... ZXDB

Can't tell what's wrong, I believe all NA inputs were removed, so maybe I altered T3 and can no longer be used by aafTableAnn?

Thank you very much for your time.

> sessionInfo()
R version 3.5.2 (2018-12-20)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.1 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=es_AR.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=es_AR.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=es_AR.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=es_AR.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] annaffy_1.54.0           KEGG.db_3.2.3           
 [3] GO.db_3.7.0              hgu133plus2.db_3.2.3    
 [5] affycoretools_1.54.0     annotate_1.60.0         
 [7] XML_3.98-1.16            org.Hs.eg.db_3.7.0      
 [9] AnnotationDbi_1.44.0     dplyr_0.7.8             
[11] limma_3.38.3             pd.hg.u133.plus.2_3.12.0
[13] DBI_1.0.0                RSQLite_2.1.1           
[15] oligo_1.46.0             Biostrings_2.50.2       
[17] XVector_0.22.0           IRanges_2.16.0          
[19] S4Vectors_0.20.1         Biobase_2.42.0          
[21] oligoClasses_1.44.0      BiocGenerics_0.28.0     
[23] BiocManager_1.30.4      

loaded via a namespace (and not attached):
  [1] backports_1.1.3             GOstats_2.48.0             
  [3] Hmisc_4.1-1                 plyr_1.8.4                 
  [5] lazyeval_0.2.1              GSEABase_1.44.0            
  [7] splines_3.5.2               BiocParallel_1.16.5        
  [9] GenomeInfoDb_1.18.1         ggplot2_3.1.0              
 [11] digest_0.6.18               foreach_1.4.4              
 [13] ensembldb_2.6.3             htmltools_0.3.6            
 [15] gdata_2.18.0                magrittr_1.5               
 [17] checkmate_1.9.1             memoise_1.1.0              
 [19] BSgenome_1.50.0             cluster_2.0.7-1            
 [21] gcrma_2.54.0                matrixStats_0.54.0         
 [23] R.utils_2.7.0               ggbio_1.30.0               
 [25] prettyunits_1.0.2           colorspace_1.4-0           
 [27] blob_1.1.1                  xfun_0.4                   
 [29] crayon_1.3.4                RCurl_1.95-4.11            
 [31] graph_1.60.0                genefilter_1.64.0          
 [33] bindr_0.1.1                 survival_2.43-3            
 [35] VariantAnnotation_1.28.8    iterators_1.0.10           
 [37] glue_1.3.0                  gtable_0.2.0               
 [39] zlibbioc_1.28.0             DelayedArray_0.8.0         
 [41] Rgraphviz_2.26.0            scales_1.0.0               
 [43] GGally_1.4.0                edgeR_3.24.3               
 [45] Rcpp_1.0.0                  xtable_1.8-3               
 [47] progress_1.2.0              htmlTable_1.13.1           
 [49] foreign_0.8-71              bit_1.1-14                 
 [51] OrganismDbi_1.24.0          preprocessCore_1.44.0      
 [53] Formula_1.2-3               AnnotationForge_1.24.0     
 [55] htmlwidgets_1.3             httr_1.4.0                 
 [57] gplots_3.0.1                RColorBrewer_1.1-2         
 [59] acepack_1.4.1               ff_2.2-14                  
 [61] pkgconfig_2.0.2             reshape_0.8.8              
 [63] R.methodsS3_1.7.1           nnet_7.3-12                
 [65] locfit_1.5-9.1              tidyselect_0.2.5           
 [67] rlang_0.3.1                 reshape2_1.4.3             
 [69] munsell_0.5.0               tools_3.5.2                
 [71] stringr_1.3.1               knitr_1.21                 
 [73] bit64_0.9-7                 caTools_1.17.1.1           
 [75] purrr_0.2.5                 AnnotationFilter_1.6.0     
 [77] bindrcpp_0.2.2              RBGL_1.58.1                
 [79] R.oo_1.22.0                 biomaRt_2.38.0             
 [81] compiler_3.5.2              rstudioapi_0.9.0           
 [83] curl_3.3                    affyio_1.52.0              
 [85] PFAM.db_3.7.0               tibble_2.0.1               
 [87] geneplotter_1.60.0          stringi_1.2.4              
 [89] GenomicFeatures_1.34.1      lattice_0.20-38            
 [91] ProtGenerics_1.14.0         Matrix_1.2-15              
 [93] pillar_1.3.1                data.table_1.12.0          
 [95] bitops_1.0-6                rtracklayer_1.42.1         
 [97] GenomicRanges_1.34.0        R6_2.3.0                   
 [99] latticeExtra_0.6-28         affy_1.60.0                
[101] hwriter_1.3.2               KernSmooth_2.23-15         
[103] gridExtra_2.3               affxparser_1.54.0          
[105] codetools_0.2-16            dichromat_2.0-0            
[107] gtools_3.8.1                assertthat_0.2.0           
[109] SummarizedExperiment_1.12.0 DESeq2_1.22.2              
[111] Category_2.48.0             ReportingTools_2.22.1      
[113] GenomicAlignments_1.18.1    Rsamtools_1.34.0           
[115] GenomeInfoDbData_1.2.0      hms_0.4.2                  
[117] grid_3.5.2                  rpart_4.1-13               
[119] biovizBase_1.30.1           base64enc_0.1-3

Your first recourse should be to read the help page for the function you are using. In this case, it says:

aafTableAnn              package:annaffy               R Documentation

Constructor for aafTable objects from annotation data

Description:

     Constructs an 'aafTable' object given a set of probe ids and
     desired annotation types.

Usage:

     aafTableAnn(probeids, chip, colnames = aaf.handler(chip = chip), widget = FALSE)

Arguments:

probeids: character vector of probe ids

And you can then immediately see where you went wrong (and if you can't see it, do note that you are passing in HUGO gene symbols, which are not probe IDs).

Anyway, for something that was apparently written a couple of years ago, the webpage you are following is pretty outdated. A much better way to proceed (IMO) is to use Glimma rather than annaffy, which was pretty sweet in its day, but that was over a decade ago. You can add annotation to your MArrayLM object using my affycoretools package:

library(affycoretools)
eset <- annotateEset(eset, hgu133plus2.db)

And then you can make an interactive plot with Glimma using glMDPlot. I leave it up to you to read the vignette for Glimma, as well as the help pages.