Question: Agilent Data Normalization Result
0
gravatar for nvayin
3.8 years ago by
nvayin0
United Kingdom
nvayin0 wrote:

I have an Agilent data set , and normalized and read it using the code bellow , but the result is different from what the paper claim.

library("limma", lib.loc="~/R/win-library/3.1")
targets<-readTargets("target2.txt",row.names=1,sep="")
targets$Filenames[!file.exists(targets$Filenames)]
x <- read.maimages(targets$Filenames,source="agilent", green.only=TRUE)
y <- backgroundCorrect(x,method="normexp")
NormData<-normalizeBetweenArrays(y,method="quantile")

R • 1.5k views
ADD COMMENTlink modified 3.8 years ago by Gordon Smyth950 • written 3.8 years ago by nvayin0

Do the paper provide code to get their result? Have you contacted the authors?

ADD REPLYlink written 3.8 years ago by andrew.j.skelton735.8k

The paper used  GX gene spring to normalize the data , i contact the authors but they are not replying 

ADD REPLYlink written 3.8 years ago by nvayin0

hello,

I have one query what type of data we put in target2.txt file...

ADD REPLYlink modified 3.4 years ago • written 3.4 years ago by sainiisha220
0
gravatar for Gordon Smyth
3.8 years ago by
Gordon Smyth950
Australia
Gordon Smyth950 wrote:

You posted the same question to the Bioconductor mailing list, and it has been answered there:

  https://support.bioconductor.org/p/73494/

ADD COMMENTlink modified 3.8 years ago • written 3.8 years ago by Gordon Smyth950

I can not figure out why my result is different? i do not what GX gene spring is doing , what the paper said is :

stander Agilent normalize methods ? i do not know what is ?

Extracted data were analysed using GeneSpring GX
7.3.1 (Silicon Genetics, USA). Agilent standard scenario
normalizations for FE1-colour arrays were applied to all
data sets. A subset of genes for data interrogation was
generated that excluded spots of poor quality, and gene
probes that were expressed in <50% of samples. 

ADD REPLYlink written 3.8 years ago by nvayin0
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