
Hello, I'm trying to analyze 11 samples from illumina HT12 chips. In the lumi package I set Although I set convert NuID and input annotation to be true, after using limma my top table does not show the gene symbol or name. 

Loading required package: annotate
          ID geneSymbol geneName    logFC  AveExpr         t
4894 2230037         NA       NA 11.93955 12.13396 100.74365
1211  610112         NA       NA 11.55668 11.63635  99.67799
I was wondering how I'd be able to add this information and export it. 
Any help would be greatly appreciated!



> sessionInfo()

R version
2.12.2 (2011-02-25)

Platform:
i386-pc-mingw32/i386 (32-bit)

 

locale:

[1]
LC_COLLATE=English_Canada.1252 
LC_CTYPE=English_Canada.1252   

[3]
LC_MONETARY=English_Canada.1252 LC_NUMERIC=C                   

[5]
LC_TIME=English_Canada.1252    

 

attached base
packages:

[1]
stats     graphics  grDevices utils     datasets 
methods   base     

 

other
attached packages:

[1]
annotate_1.28.0       
lumiHumanAll.db_1.12.0 org.Hs.eg.db_2.4.6    

[4]
RSQLite_0.9-2          DBI_0.2-5              AnnotationDbi_1.12.0  

[7]
limma_3.6.9            lumi_2.2.1             Biobase_2.10.0        

 

loaded via a
namespace (and not attached):

 [1] affy_1.28.0           affyio_1.18.0         grid_2.12.0          

 [4] hdrcde_2.15           KernSmooth_2.23-4     lattice_0.19-13      

 [7] MASS_7.3-8            Matrix_0.999375-44    methylumi_1.6.1      

[10]
mgcv_1.6-2            nlme_3.1-97           preprocessCore_1.12.0

[13]
tools_2.12.0          xtable_1.5-6      

 

#------------------------------------------------------------#


###HT-12 illumina data.
11samples, 3 groups 

#group1:AJ

#group2:BCDH

#group3:EFGIKL

#------------------------------------------------------------#

 

###PREAMBLE###############################

library("lumi");

date <- Sys.Date();

 

####################################################

setwd("\\\\rinas1p2/users/ramank/Illumina/NugenAnalysis")

#load raw data

data<-
"FinalReportA-K.txt";

#read data

x.lumi<-lumiR(fileName=data,

                                                sep="\t",

                                                detectionTh=0.01,

                                                na.rm=TRUE,

                                                convertNuID=TRUE,

                                                lib.mapping=NULL,

                                                dec='.',

                                                parseColumnName=TRUE,

                                                checkDupId=TRUE,

                                                QC=TRUE,

                                                columnNameGrepPattern=list(exprs='AVG_Signal',

                                                                                                                                se.exprs='BEAD_STDERR',

                                                                                                                                detection='Detection
Pval',

                                                                                                                                beadNum='Avg_NBEADS'),

                                                inputAnnotation=TRUE,

                                                annotationColumn=c('ACCESSION',

                                                                                                'SYMBOL',

                                                                                                'PROBE_START',

                                                                                                'CHROMOSOME',

                                                                                                'PROBE_CHR_ORIENTATION',

                                                                                                'PROBE_COORDINATES',

                                                                                                'DEFINITION'),

                                                verbose=TRUE);



#summary of the quality
control

summary(x.lumi, 'QC');

##????how to write this to
a txt file?????##



#########2 PRE PROCESSING
METHODS (LUMI)################## ############

###no background
correction since no control, 

#variance stabilization =
log2

#normalization  = quantile



noBg_log_quantile <-
lumiExpresso(

                                                                                                x.lumi,


                                                                                                bg.correct
= TRUE, 

                                                                                                bgcorrect.param
= list(method='none'), 

                                                                                                variance.stabilize
= TRUE, 

                                                                                                varianceStabilize.param
= list(method='log2'), 

                                                                                                normalize
= TRUE, 

                                                                                                normalize.param
= list(method='quantile'),    

                                                                                                QC.evaluation
= TRUE, 

                QC.param = list(), verbose = TRUE)



summary(noBg_log_quantile,'QC')   





#making matrix of the data

lumi.N.Q <-
noBg_log_quantile

dataMatrix <-
exprs(lumi.N.Q);



#filtering

presentCount <-
detectionCall(x.lumi);

selDataMatrix <-
dataMatrix[presentCount > 0,];

probeList <-
rownames(selDataMatrix);



####################################################################

## LIMMA

####################################################################



SampleType <-
c('1','2','2','2','3','3','3','2','3','1','3')

##????above line correct?????##





if (require(limma)) {

                ##  compare '1'
and '2' and '3'

                design <- model.matrix(~ factor(sampleType))

                colnames(design) <- c('1', '2', '3')

                fit <- lmFit(selDataMatrix, design)

                fit <- eBayes(fit)

                ## Add gene symbols to gene properties

                                if (require(lumiHumanAll.db) &
require(annotate)) {

               geneSymbol <-
getSYMBOL(probeList, 'lumiHumanAll.db')

               geneName <-
sapply(lookUp(probeList, 'lumiHumanAll.db', 'GENENAME'), function(x) x[1])

               fit$genes <- data.frame(ID=
probeList, geneSymbol=geneSymbol, geneName=geneName, stringsAsFactors=FALSE)

          }

                ## print the top 10 genes

                print(topTable(fit, coef='1', adjust='fdr',
number=10))

                

                ## get significant gene list with FDR adjusted
p.values less than 0.01

                p.adj <- p.adjust(fit$p.value[,2])                        

                sigGene.adj <- probeList[ p.adj < 0.01]

                ## without FDR adjustment

                sigGene <- probeList[ fit$p.value[,2] < 0.01]

} ;


.kripa 		 	   		  
	[[alternative HTML version deleted]]

