[BioC] Remove samples and probes from Illumina 450K data

[Donglei Hu [guest]]

Hi,

I have Illumina 450K data for 570 samples.  I have loaded IDAT files into R using minfi.  After I ran some QC steps, I'd like to remove sample outliers and probes with large detection P.  Is there a straightforward way to do so in minfi?  I have searched in Bioconductor mailing list but couldn't find a direct answer.  Thank you very much for the help!

Donglei Hu, Ph.D.
Department of Medicine
University of California, San Francisco

 -- output of sessionInfo(): 

R version 2.15.3 (2013-03-01)
Platform: x86_64-pc-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=C                 LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] IlluminaHumanMethylation450kmanifest_0.4.0
 [2] minfi_1.4.0                               
 [3] Biostrings_2.26.3                         
 [4] GenomicRanges_1.10.7                      
 [5] IRanges_1.16.6                            
 [6] reshape_0.8.4                             
 [7] plyr_1.8                                  
 [8] lattice_0.20-15                           
 [9] Biobase_2.18.0                            
[10] BiocGenerics_0.4.0                        

loaded via a namespace (and not attached):
 [1] affyio_1.26.0         annotate_1.36.0       AnnotationDbi_1.20.7 
 [4] beanplot_1.1          BiocInstaller_1.8.3   bit_1.1-10           
 [7] codetools_0.2-8       crlmm_1.16.9          DBI_0.2-7            
[10] ellipse_0.3-8         ff_2.2-11             foreach_1.4.1        
[13] genefilter_1.40.0     grid_2.15.3           iterators_1.0.6      
[16] limma_3.14.4          MASS_7.3-23           Matrix_1.0-12        
[19] matrixStats_0.8.1     mclust_4.1            multtest_2.14.0      
[22] mvtnorm_0.9-9995      nor1mix_1.1-4         oligoClasses_1.20.0  
[25] parallel_2.15.3       preprocessCore_1.20.0 RColorBrewer_1.0-5   
[28] RcppEigen_0.3.1.2.1   R.methodsS3_1.4.4     RSQLite_0.11.4       
[31] siggenes_1.32.0       splines_2.15.3        stats4_2.15.3        
[34] survival_2.37-4       XML_3.98-1.1          xtable_1.7-1         
[37] zlibbioc_1.4.0


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