[BioC] sample probe profile or sample gene profile

Francisco Ortuno [guest] guest at bioconductor.org
Mon Jul 1 12:51:15 CEST 2013


R version 2.15.0 (2012-03-30)
Platform: x86_64-pc-mingw32/x64 (64-bit)

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

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

other attached packages:
 [1] limma_3.12.3               lumiHumanIDMapping_1.10.0 
 [3] arrayQualityMetrics_3.12.0 lumiHumanAll.db_1.18.0    
 [5] org.Hs.eg.db_2.7.1         RSQLite_0.11.4            
 [7] DBI_0.2-7                  annotate_1.34.1           
 [9] AnnotationDbi_1.18.4       lumi_2.8.0                
[11] nleqslv_2.0                methylumi_2.2.0           
[13] ggplot2_0.9.3.1            reshape2_1.2.2            
[15] scales_0.2.3               Biobase_2.16.0            
[17] BiocGenerics_0.2.0        

loaded via a namespace (and not attached):
 [1] affy_1.34.0           affyio_1.24.0         affyPLM_1.32.0       
 [4] beadarray_2.6.0       BeadDataPackR_1.8.0   bigmemory_4.2.11     
 [7] BiocInstaller_1.4.9   Biostrings_2.24.1     bitops_1.0-5         
[10] BSgenome_1.24.0       Cairo_1.5-2           cluster_1.14.4       
[13] colorspace_1.2-2      dichromat_2.0-0       digest_0.6.3         
[16] DNAcopy_1.30.0        genefilter_1.38.0     GenomicRanges_1.8.13 
[19] genoset_1.6.0         grid_2.15.0           gtable_0.1.2         
[22] hdrcde_2.16           Hmisc_3.10-1.1        hwriter_1.3          
[25] IRanges_1.14.4        KernSmooth_2.23-10    labeling_0.2         
[28] lattice_0.20-6        latticeExtra_0.6-24   MASS_7.3-23          
[31] Matrix_1.0-12         mgcv_1.7-24           munsell_0.4          
[34] nlme_3.1-108          plyr_1.8              preprocessCore_1.18.0
[37] proto_0.3-10          RColorBrewer_1.0-5    RCurl_1.95-4.1       
[40] Rsamtools_1.8.6       rtracklayer_1.16.3    setRNG_2011.11-2     
[43] splines_2.15.0        stats4_2.15.0         stringr_0.6.2        
[46] survival_2.37-4       SVGAnnotation_0.93-1  tools_2.15.0         
[49] vsn_3.24.0            XML_3.98-1.1          xtable_1.7-1         
[52] zlibbioc_1.2.0 


 -- output of sessionInfo(): 

Hi,

I'm trying to perform an analysis of differential expression between control and patients groups from Illumina microarray data. I have read the vignette of the "lumi" package and some others works related to Illumina microarrays but I'm still not sure if I have to use gene profile or probe profile files. 

What are the advantages or disadvantages of each one? Which one is the most adequate for this kind of analyses?

Thank you very much in advance,

Francisco.


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