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Gene Expression analysis of Clariom D array

Hello All Recently i got clariom D samples As of now i am using TAC (Affymetrix tool)and bioconductor package and comparing results of both My bioconductor code is :

setwd("Path to my cel files")
library(oligo)
library(affycoretools)
library(limma)
library(clariomdhumantranscriptcluster.db)
library(pd.clariom.d.human)
list.celfiles()
T1.cel
T2.cel
T3.cel
C1.cel
C2.cel
C3.cel
dat <- read.celfiles(list.celfiles())

probeset.eset=rma(dat,target="core")

probeset.eset <- annotateEset(probeset.eset,annotation(probeset.eset))

strain <- c("Test","Test","Test","Control","Control","Control")
x <- model.matrix(~factor(strain))
design
colnames(x) <- c("Test vs Control","Control")

>x
Test vs Control Control
1               1       1
2               1       1
3               1       1
4               1       0
5               1       0
6               1       0
attr(,"assign")
[1] 0 1
attr(,"contrasts")
attr(,"contrasts")$`factor(strain)`
"contr.treatment"**



fit3 <- lmFit(probeset.eset,design = x)
fit3<- eBayes(fit3)
options(digits=2)
r6<-topTable(fit = fit3,coef=2, n=10000, adjust="BY")
write.csv(r5,"C://Users/Clariom-D/Clariom_7_17/reult.csv")

When i compare DGE expressing of gene say x from limma pipeline i am getting value -1.91 and from TAC software i am getting value -13

Why there is so much difference between the two? Which pipeline should i consider to be better?

Is there any mistake i am doing if so what that mistake is and how to rectify?

sessionInfo()
R version 3.3.3 (2017-03-06)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

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] pd.clariom.d.human_3.14.1               DBI_0.7                                
 [3] RSQLite_2.0                             clariomdhumantranscriptcluster.db_8.5.0
 [5] org.Hs.eg.db_3.4.0                      AnnotationDbi_1.36.2                   
 [7] limma_3.30.13                           affycoretools_1.46.5                   
 [9] oligo_1.38.0                            Biostrings_2.42.1                      
[11] XVector_0.14.1                          IRanges_2.8.2                          
[13] S4Vectors_0.12.2                        Biobase_2.34.0                         
[15] oligoClasses_1.36.0                     BiocGenerics_0.20.0                    

loaded via a namespace (and not attached):
  [1] colorspace_1.3-2              hwriter_1.3.2                
  [3] biovizBase_1.22.0             htmlTable_1.9                
  [5] GenomicRanges_1.26.4          base64enc_0.1-3              
  [7] dichromat_2.0-0               affyio_1.44.0                
  [9] bit64_0.9-7                   interactiveDisplayBase_1.12.0
 [11] codetools_0.2-15              splines_3.3.3                
 [13] R.methodsS3_1.7.1             ggbio_1.22.4                 
 [15] geneplotter_1.52.0            knitr_1.16                   
 [17] Formula_1.2-2                 Rsamtools_1.26.2             
 [19] annotate_1.52.1               cluster_2.0.5                
 [21] GO.db_3.4.0                   R.oo_1.21.0                  
 [23] graph_1.52.0                  shiny_1.0.3                  
 [25] httr_1.2.1                    GOstats_2.40.0               
 [27] backports_1.1.0               Matrix_1.2-8                 
 [29] lazyeval_0.2.0                acepack_1.4.1                
 [31] htmltools_0.3.6               tools_3.3.3                  
 [33] affy_1.52.0                   gtable_0.2.0                 
 [35] Category_2.40.0               reshape2_1.4.2               
 [37] affxparser_1.46.0             Rcpp_0.12.12                 
 [39] gdata_2.18.0                  preprocessCore_1.36.0        
 [41] rtracklayer_1.34.2            iterators_1.0.8              
 [43] stringr_1.2.0                 mime_0.5                     
 [45] ensembldb_1.6.2               gtools_3.5.0                 
 [47] XML_3.98-1.9                  AnnotationHub_2.6.5          
 [49] edgeR_3.16.5                  zlibbioc_1.20.0              
 [51] scales_0.4.1                  BSgenome_1.42.0              
 [53] VariantAnnotation_1.20.3      BiocInstaller_1.24.0         
 [55] SummarizedExperiment_1.4.0    RBGL_1.50.0                  
 [57] RColorBrewer_1.1-2            yaml_2.1.14                  
 [59] memoise_1.1.0                 gridExtra_2.2.1              
 [61] ggplot2_2.2.1                 biomaRt_2.30.0               
 [63] rpart_4.1-10                  gcrma_2.46.0                 
 [65] reshape_0.8.6                 latticeExtra_0.6-28          
 [67] stringi_1.1.5                 genefilter_1.56.0            
 [69] foreach_1.4.3                 checkmate_1.8.3              
 [71] caTools_1.17.1                GenomicFeatures_1.26.4       
 [73] BiocParallel_1.8.2            GenomeInfoDb_1.10.3          
 [75] ReportingTools_2.14.0         rlang_0.1.1                  
 [77] pkgconfig_2.0.1               bitops_1.0-6                 
 [79] lattice_0.20-34               GenomicAlignments_1.10.1     
 [81] htmlwidgets_0.9               bit_1.1-12                   
 [83] GSEABase_1.36.0               AnnotationForge_1.16.1       
 [85] GGally_1.3.1                  plyr_1.8.4                   
 [87] magrittr_1.5                  DESeq2_1.14.1                
 [89] R6_2.2.2                      gplots_3.0.1                 
 [91] Hmisc_4.0-3                   foreign_0.8-67               
 [93] survival_2.41-3               RCurl_1.95-4.8               
 [95] nnet_7.3-12                   tibble_1.3.3                 
 [97] KernSmooth_2.23-15            OrganismDbi_1.16.0           
 [99] PFAM.db_3.4.0                 locfit_1.5-9.1               
[101] grid_3.3.3                    data.table_1.10.4            
[103] blob_1.1.0                    digest_0.6.12                
[105] xtable_1.8-2                  ff_2.2-13                    
[107] httpuv_1.3.5                  R.utils_2.5.0                
[109] munsell_0.4.3
clariom d gene expression

1 answer

Hi, I am only providing an answer because I happen to be processing a Clariom array.

It could be related to many things, one being a different normalisation procedure: A: RMA with Affymetrix Expression Console vs Oligo package

Kevin

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