Hello Aroma developers,

Attached session info and code. Platform windows. 
I'm following steps 
on http://www.aroma-project.org/vignettes/FIRMA-HumanExonArrayAnalysis/

In brief: I do background correct, normal quantile and perform ExonRmaPlm  

I'm unable to decide and understand difference between ExonRmaPlm 
and RmaPlm. Could the developers please shade light to when to use RmaPlm 
in aroma?

Thanks.

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R version 3.4.3 (2017-11-30)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

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] aroma.light_3.8.0        aroma.affymetrix_3.1.0   aroma.core_3.1.1         
R.devices_2.15.1        
 [5] R.filesets_2.12.1        R.utils_2.6.0            R.oo_1.21.0              
affxparser_1.50.0       
 [9] R.methodsS3_1.7.1        limma_3.34.9             BiocInstaller_1.28.0     
Cairo_1.5-9             
[13] annotate_1.56.2          XML_3.98-1.10            AnnotationDbi_1.40.0     
pd.huex.1.0.st.v2_3.14.1
[17] DBI_0.8                  RSQLite_2.0              ff_2.2-13                
bit_1.1-12              
[21] oligo_1.42.0             Biostrings_2.46.0        XVector_0.18.0           
IRanges_2.12.0          
[25] S4Vectors_0.16.0         Biobase_2.38.0           oligoClasses_1.40.0      
BiocGenerics_0.24.0     

loaded via a namespace (and not attached):
 [1] SummarizedExperiment_1.8.1 R.huge_0.9.0               DNAcopy_1.52.0       
     
 [4] listenv_0.7.0              splines_3.4.3              lattice_0.20-35      
     
 [7] base64enc_0.1-3            blob_1.1.1                 bit64_0.9-7          
     
[10] affyio_1.48.0              matrixStats_0.53.1         
GenomeInfoDbData_1.0.0    
[13] foreach_1.4.4              R.cache_0.13.0             zlibbioc_1.24.0      
     
[16] future_1.8.0               codetools_0.2-15           memoise_1.1.0        
     
[19] GenomeInfoDb_1.14.0        preprocessCore_1.40.0      Rcpp_0.12.16         
     
[22] xtable_1.8-2               DelayedArray_0.4.1         PSCBS_0.63.0         
     
[25] R.rsp_0.42.0               digest_0.6.15              GenomicRanges_1.30.3 
     
[28] grid_3.4.3                 tools_3.4.3                bitops_1.0-6         
     
[31] RCurl_1.95-4.10            future.apply_0.1.0         pkgconfig_2.0.1      
     
[34] Matrix_1.2-12              iterators_1.0.9            aroma.apd_0.6.0      
     
[37] globals_0.11.0             compiler_3.4.3            
cdf <- AffymetrixCdfFile$byChipType("HuEx-1_0-st-v2")
print(cdf)
cdf <- AffymetrixCdfFile$byChipType("HG-U133_Plus_2")


cs <- AffymetrixCelSet$byName("celfiles", cdf=cdf) # rawdata in cwd. 
HuEx-1_0-st-v2 in celfiles # this should match cdf file names too
print(cs)
bc <- RmaBackgroundCorrection(cs) #backgroun
csBC <- process(bc,verbose=verbose)

qn <- QuantileNormalization(csBC, typesToUpdate="pm") #quantile norm
csN <- process(qn, verbose=verbose)

getCdf(csN) ##get CDF infor

plmTr <- ExonRmaPlm(csN, mergeGroups=TRUE) #entrire transcript #for 
exon-by-exon mergeGroup make FALSE
print(plmTr)

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