Package gcrma: unused argument (validate = FALSE)
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@zhangjianhai-12955
Last seen 4.9 years ago

Hello, Bioconductor communities,

I am using the function "gcrma (data, fast = T)" from package "gcrma", where "data" is an "AffyBatch", but it always gives "Adjusting for optical effect.Error in assayDataElementReplace(object, "exprs", value, validate = FALSE) : unused argument (validate = FALSE)"

Does anyone know how to resolve?

Thanks,

Jianhai
gcrma • 1.8k views
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Guido Hooiveld ★ 4.1k
@guido-hooiveld-2020
Last seen 1 day ago
Wageningen University, Wageningen, the …

Mmm, you don't provide much info for anyone to help troubleshooting..... First of all, which type of array do you want to normalize? Also, please show the full code you used as well as output from sessionInfo().

 

<<EDIT>> As can be seen in my (first) comment below, your code is working fine on my system [using the latest R/BioC].
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Hello,

The relevant code is below:

> con.mo
 [1] "GSM361976.cel" "GSM361977.cel" "GSM361980.cel" "GSM361981.cel"
 [5] "GSM361984.cel" "GSM361985.cel" "GSM361988.cel" "GSM361989.cel"
 [9] "GSM361992.cel" "GSM361993.cel" "GSM362168.CEL" "GSM362169.CEL"
[13] "GSM362170.CEL" "GSM362171.CEL" "GSM362175.CEL" "GSM362176.CEL"
[17] "GSM362177.CEL" "GSM362180.CEL" "GSM362181.CEL" "GSM362184.CEL"
[21] "GSM362185.CEL" "GSM362188.CEL" "GSM362189.CEL" "GSM362192.CEL"
[25] "GSM362193.CEL" "GSM362194.CEL" "GSM362197.CEL" "GSM362198.CEL"
[29] "GSM362201.CEL" "GSM362202.CEL" "GSM362203.CEL" "GSM362204.CEL"
[33] "GSM362207.CEL" "GSM362208.CEL" "GSM362211.CEL" "GSM362212.CEL"
[37] "GSM362215.CEL" "GSM362216.CEL" "GSM362217.CEL" "GSM362221.CEL"
[41] "GSM362222.CEL" "GSM362225.CEL" "GSM362226.CEL" "GSM362229.CEL"
[45] "GSM362230.CEL" "GSM362233.CEL" "GSM362234.CEL" "GSM362237.CEL"
[49] "GSM362238.CEL" "GSM362239.CEL" "GSM362240.CEL" "GSM362243.CEL"
[53] "GSM362244.CEL"

 data <- ReadAffy(filenames = con.mo, celfile.path="GSE14578_RAW_cel")

> data
AffyBatch object
size of arrays=712x712 features (32 kb)
cdf=ATH1-121501 (22810 affyids)
number of samples=53
number of genes=22810
annotation=ath1121501
notes=

 

> gc.nor <- gcrma(data, fast = T)                                                               
Adjusting for optical effect.Error in assayDataElementReplace(object, "exprs", value, validate = FALSE) : 
  unused argument (validate = FALSE)

 

 

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It is working for me!?!

I downloaded all 99 (compressed) CEL files from the GEO experiment you mentioned (GSE14578), loaded them all into R, and then performed gcRMA normalization. As said before, without any problems.

The only things I can suggest is that:

- start a fresh R session (because I noticed also a CDF for mouse arrays had been loaded), and

-you may want to update the the latest version of R/BioC (v3.4.0/v3.5), since I noticed your installation is ~ 1 yr old.

 

 

I would also recommend to use the full word "TRUE" (instead of "T") when specifying the type of algorithm to be used (fast=TRUE). BTW: I would advise to use fast=FALSE, thus use the empirical Bayes approach for background estimation.

 

 

> setwd("D:\\DIR\\with\\CELFiles") #set working directory to DIR containing the (compressed) CEL files
> library(affy)
> library(gcrma)
> dir()
 [1] "GSM361976.cel.gz" "GSM361977.cel.gz" "GSM361978.cel.gz" "GSM361979.cel.gz"
<<SNIP>>
[97] "GSM362244.CEL.gz" "GSM362245.CEL.gz" "GSM362246.CEL.gz"
>
> data <- ReadAffy()
> data

AffyBatch object
size of arrays=712x712 features (49 kb)
cdf=ATH1-121501 (22810 affyids)
number of samples=99
number of genes=22810
annotation=ath1121501
notes=

>
> gc.nor <- gcrma(data, fast = TRUE)
Adjusting for optical effect..............................................................Done.
Computing affinities.Done.
Adjusting for non-specific binding.......................................................Done.
Normalizing
Calculating Expression

> gc.nor
ExpressionSet (storageMode: lockedEnvironment)
assayData: 22810 features, 99 samples
  element names: exprs
protocolData
  sampleNames: GSM361976.cel.gz GSM361977.cel.gz ... GSM362246.CEL.gz (99 total)
  varLabels: ScanDate
  varMetadata: labelDescription
phenoData
  sampleNames: GSM361976.cel.gz GSM361977.cel.gz ... GSM362246.CEL.gz (99 total)
  varLabels: sample
  varMetadata: labelDescription
featureData: none
experimentData: use 'experimentData(object)'
Annotation: ath1121501
>

> exprs(gc.nor)[1:5,1:10]
          GSM361976.cel.gz GSM361977.cel.gz GSM361978.cel.gz GSM361979.cel.gz GSM361980.cel.gz
244901_at         2.170775         2.123745         2.123745         2.123745         2.123745
244902_at         2.339522         2.171223         2.124894         2.230952         2.124894
244903_at         2.416259         2.435598         2.370497         2.370497         2.416259
244904_at         2.104487         2.104487         2.104487         2.104487         2.104487
244905_at         2.104487         2.104487         2.104487         2.104487         2.104487
          GSM361981.cel.gz GSM361982.cel.gz GSM361983.cel.gz GSM361984.cel.gz GSM361985.cel.gz
244901_at         2.123745         2.123745         2.104487         2.187697         2.123745
244902_at         2.123087         2.124894         2.124894         2.124894         2.123087
244903_at         2.104487         2.435598         7.033798         4.979040         2.889587
244904_at         2.104487         2.104487         2.104487         2.104487         2.104487
244905_at         2.104487         2.104487         2.104487         2.104487         2.173172
>

 

> sessionInfo()
R version 3.4.0 Patched (2017-05-10 r72670)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

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

other attached packages:
[1] ath1121501probe_2.18.0 AnnotationDbi_1.38.0   IRanges_2.10.2         S4Vectors_0.14.2      
[5] ath1121501cdf_2.18.0   gcrma_2.48.0           affy_1.52.0            Biobase_2.36.2        
[9] BiocGenerics_0.22.0   

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.11          Biostrings_2.44.0     digest_0.6.12         DBI_0.6-1            
 [5] RSQLite_1.1-2         BiocInstaller_1.26.0  zlibbioc_1.22.0       XVector_0.16.0       
 [9] affyio_1.46.0         preprocessCore_1.38.1 splines_3.4.0         tools_3.4.0          
[13] compiler_3.4.0        memoise_1.1.0        
>
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Dear Guido Hooiveld,

It works well when I started a fresh R session of version 3.3, or version 3.4., as you suggested.

Thank you very much!!

Regards,

Jianhai

 

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> sessionInfo()
R version 3.3.0 (2016-05-03)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

locale:
[1] C

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

other attached packages:
 [1] mouse4302cdf_2.18.0   xtable_1.8-2          KEGG.db_3.2.3        
 [4] gcrma_2.46.0          eisa_1.26.0           isa2_0.3.5           
 [7] GEOquery_2.40.0       BiocInstaller_1.24.0  clusterProfiler_3.0.5
[10] DOSE_2.10.7           Rgraphviz_2.18.0      GO.db_3.4.0          
[13] ath1121501cdf_2.18.0  GOstats_2.40.0        graph_1.52.0         
[16] ath1121501.db_3.2.3   org.At.tair.db_3.4.0  Category_2.40.0      
[19] Matrix_1.2-8          AnnotationDbi_1.36.2  IRanges_2.8.1        
[22] S4Vectors_0.12.1      gplots_3.0.1          ape_4.1              
[25] limma_3.30.11         affy_1.52.0           Biobase_2.32.0       
[28] BiocGenerics_0.20.0  

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.10           lattice_0.20-34        tidyr_0.6.1           
 [4] Biostrings_2.42.1      gtools_3.5.0           assertthat_0.1        
 [7] digest_0.6.12          R6_2.2.0               plyr_1.8.4            
[10] RSQLite_1.1-2          httr_1.2.1             ggplot2_2.2.1         
[13] zlibbioc_1.20.0        lazyeval_0.2.0         annotate_1.52.1       
[16] gdata_2.17.0           SparseM_1.77           preprocessCore_1.36.0 
[19] qvalue_2.6.0           splines_3.3.0          stringr_1.2.0         
[22] topGO_2.26.0           igraph_1.0.1           RCurl_1.95-4.8        
[25] munsell_0.4.3          tcltk_3.3.0            tibble_1.2            
[28] matrixStats_0.51.0     XML_3.98-1.5           AnnotationForge_1.16.0
[31] bitops_1.0-6           RBGL_1.50.0            nlme_3.1-131          
[34] GSEABase_1.36.0        gtable_0.2.0           DBI_0.5-1             
[37] magrittr_1.5           scales_0.4.1           KernSmooth_2.23-15    
[40] stringi_1.1.2          GOSemSim_2.0.4         XVector_0.14.0        
[43] reshape2_1.4.2         genefilter_1.56.0      affyio_1.44.0         
[46] DO.db_2.9              tools_3.3.0            survival_2.40-1       
[49] colorspace_1.3-2       caTools_1.17.1         memoise_1.0.0     

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