Dear James, 

Many thanks for your quick and easy understable question. I would like to ask you if you could recommend me a method to determine which point could be considered as level for distinguishing expression values from noise? 

Juan 

--------------------------------------------------------------- 
Juan Fernandez Tajes, ph. D 
Grupo XENOMAR 
Departamento de Biología Celular y Molecular 
Facultad de Ciencias-Universidade da Coruña 
Tlf. +34 981 167000 ext 2030 
e-mail: jfernandezt@udc.es 
---------------------------------------------------------------- 



De: "James W. MacDonald" <jmacdon@uw.edu> 
Para: "Juan Fernández Tajes" <jfernandezt@udc.es> 
CC: "bioconductor" <bioconductor@r-project.org> 
Enviados: Viernes, 28 de Septiembre 2012 16:48:10 
Asunto: Re: [BioC] Analyzing expression Affymetrix Hugene1.0.st array 

Hi Juan, 

On 9/28/2012 6:10 AM, Juan Fernández Tajes wrote: 
> Dear List, 
> 
> IÂ´m working with expression data obtained from Affymetrix HuGene 1.0 st array. IÂ´m interested in knowing how many genes are expressed in chromosome 16. Surprisingly, all the genes included (808) in the array and mapped to chromosome have expression values (from 2.01 to 12.4), can I conclude that all these genes are expressed in this tissue? 

Not really. Microarrays are not suitable for determining if a gene is 
being expressed or not. The only use IMO of microarray data is to 
determine if a gene is *differentially* expressed. This is what Benilton 
is getting at in his response to your question. 

The expression values we generate from a set of microarrays are very far 
removed from the actual amount of mRNA that existed in the samples we 
are measuring, and have undergone quite a bit of manipulation. In 
addition, there is quite a bit of technical noise introduced in each 
step of the process. So the best we can hope for is that the expression 
value for a given gene is proportional to the amount of mRNA that 
existed in the original sample, but not that we are quantifying the 
amount of mRNA. 

In addition, the expression values are based off of data from a 16 bit 
TIFF image. So the values have a maximum range from 2^0 - 2^16, or 
1-65535 on the natural scale. Given that fact, do you really want to 
contend that a gene with an expression of 2^2.01 is being expressed? 
That expression level is likely not distinguishable from noise. So one 
more difficulty in deciding if a gene is expressed is deciding at which 
point you can distinguish signal from underlying noise. 

Best, 

Jim 


> 
> Many thanks in advance 
> 
> Here is my code: 
> 
> 
> geneCELs.N<- list.celfiles(getwd(), full.names=T) 
> affyGeneFS.N<- read.celfiles(geneCELs.N) 
> myAB.N<- affyGeneFS.N 
> sampleNames(myAB.N)<- sub("\\.CEL$", "", sampleNames(myAB.N)) 
> sampleNames(myAB.N)<- sub("\\.CEL$", "", sampleNames(myAB.N)) 
> metadata_array.N<- read.delim(file="metadata.txt", header=T, sep="\t") 
> rownames(metadata_array.N)<- metadata_array.N$Sample_ID 
> phenoData(myAB.N)<- new("AnnotatedDataFrame", data=metadata_array.N) 
> myAB.N_rma<- rma(myAB.N, target="core") 
> annotation(myAB.N_rma)<- "hugene10sttranscriptcluster.db" 
> 
> ppc<- function(x) paste("^", x, sep="") 
> myFindMap<- function(mapEnv, which){ 
> myg<- ppc(which) 
> a1 = eapply(mapEnv, function(x) 
> grep(myg, x, value=T)) 
> unlist(a1) 
> } 
> chr16.N<- myFindMap(hugene10sttranscriptclusterCHR, 16) 
> chr16.N<- as.data.frame(chr16.N) 
> chr16.N$probes<- rownames(chr16.N) 
> probes.chr16.N<- chr16.N$probes 
> sel.N<- match(probes.chr16.N, featureNames(myAB.N_rma), nomatch=0) 
> es2_chr16.N<- myAB.N_rma[sel.N,] 
> data.exprs.N<- as.data.frame(exprs(es2_chr16.N)) 
> g.N<- featureNames(es2_chr16.N) 
> linked.N<- links(hugene10sttranscriptclusterSYMBOL) 
> data.exprs.N.symbol<- merge(data.exprs.N, linked.N, by.x="row.names", by.y="probe_id") 
> row.names(data.exprs.N.symbol)<- data.exprs.N.symbol[[1]] 
> data.exprs.N.symbol<- data.exprs.N.symbol[, -1] 
> data.exprs.N.symbol$Mean.Exprs<- rowMeans(data.exprs.N.symbol[, 1:12]) 
> 
> 
> Juan 
> 
> 
> --------------------------------------------------------------- 
> Juan Fernandez Tajes, ph. D 
> Grupo XENOMAR 
> Departamento de BiologÃ­a Celular y Molecular 
> Facultad de Ciencias-Universidade da CoruÃ±a 
> Tlf. +34 981 167000 ext 2030 
> e-mail: jfernandezt@udc.es 
> ---------------------------------------------------------------- 
> 
> 
> 
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> 
> 
> 
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-- 
James W. MacDonald, M.S. 
Biostatistician 
University of Washington 
Environmental and Occupational Health Sciences 
4225 Roosevelt Way NE, # 100 
Seattle WA 98105-6099 


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