[BioC] RMA probe summarization when sizes of probesets are unequal

Xin Lin [guest] guest at bioconductor.org
Fri Aug 16 17:50:04 CEST 2013

Dear all,

I have a customized two-channel microarray designed by NimbleGen (one of the last they produced) based on 26981 cDNA sequences of tomato. 60-mer oligonucleotide probes were designed and multiple probes were used for each transcript. The problem is, the sizes of probe-sets are not equal -- ranging from 5 to 1 (26784 of them have 5 probes).

I am now trying to use rma() in oligo for normalization and summarization. My question is, in the situation where sizes of probe-sets are unequal, how does rma() do the probe summarization? Will it be problematic if I use rma() directly? If rma() could not do the correct job, what alternative method can I use for probe summarization? 

I am new in microarray and R, and I'll appreciate your help very much! Thank you for your time!


 -- output of sessionInfo(): 

> sessionInfo()
R version 3.0.1 (2013-05-16)
Platform: x86_64-apple-darwin10.8.0 (64-bit)

[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
 [1] qvalue_1.34.0                 affyPLM_1.36.0                preprocessCore_1.22.0        
 [4] gcrma_2.32.0                  affy_1.38.1                   pd.121114.slycop.tm.exp_0.0.1
 [7] pdInfoBuilder_1.24.0          affxparser_1.32.3             oligo_1.24.0                 
[10] oligoClasses_1.22.0           geneplotter_1.38.0            lattice_0.20-15              
[13] annotate_1.38.0               AnnotationDbi_1.22.6          Biobase_2.20.1               
[16] BiocGenerics_0.6.0            RColorBrewer_1.0-5            limma_3.16.6                 
[19] genefilter_1.42.0             RSQLite_0.11.4                DBI_0.2-7                    

loaded via a namespace (and not attached):
 [1] affyio_1.28.0        BiocInstaller_1.10.2 Biostrings_2.28.0    bit_1.1-10          
 [5] codetools_0.2-8      ff_2.2-11            foreach_1.4.1        GenomicRanges_1.12.4
 [9] grid_3.0.1           IRanges_1.18.2       iterators_1.0.6      splines_3.0.1       
[13] stats4_3.0.1         survival_2.37-4      tcltk_3.0.1          tools_3.0.1         
[17] XML_3.95-0.2         xtable_1.7-1         zlibbioc_1.6.0   

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