We receive microarray data from processing facility in a simple format
o
background subtracted intensities, here's an example, tab delimited:
Gene ID C1860gu C1775gu C1777gu
AA278251 100.825641 82.30144928 222.4144928
AA401404 383.6702703 374.1666667 342.3405797
AA454191 100.7403727 175.2884199 135.4404762
AA460836 343.9164875 366.684058 351.8411658
AA723761 445.059587 451.999359 355.5185897
AA902654 400.1301282 431.4055556 367.1327381
AA905415 200.9855072 208.0207576 218.5183983
Thus, for each array (C2860gu,...) we have corresponding gene
expression
data. How to import this data into ESET object for further handling?
Thank you!
2008/5/8 Dozmorov, Mikhail G. (HSC) <mikhail-dozmorov@ouhsc.edu>:
> We receive microarray data from processing facility in a simple
format o
> background subtracted intensities, here's an example, tab delimited:
>
> Gene ID C1860gu C1775gu C1777gu
> AA278251 100.825641 82.30144928 222.4144928
> AA401404 383.6702703 374.1666667 342.3405797
> AA454191 100.7403727 175.2884199 135.4404762
> AA460836 343.9164875 366.684058 351.8411658
> AA723761 445.059587 451.999359 355.5185897
> AA902654 400.1301282 431.4055556 367.1327381
> AA905415 200.9855072 208.0207576 218.5183983
>
> Thus, for each array (C2860gu,...) we have corresponding gene
expression
> data. How to import this data into ESET object for further handling?
> Thank you!
>
>
>
Hi Mikhail,
Import into ESET I dont know how to do that, but I do something like
this:
> raw.data <- read.table("your_received_microarray_data.txt",
sep="\t",
dec=".", header=TRUE)
> raw.data
> raw.data2 <- raw.data[,2:4]
> rownames(raw.data2) <- raw.data[,1]
> raw.data2
> library(limma)
> library(affy)
> library(vsn)
> raw.data2 <- as.matrix(raw.data2)
> norm.data.quantiles <- normalize.quantiles(raw.data2)
> # for normalization process you can use vsn, or others methods.
> help.search("normalize")
> norm.data.quantiles
> rownames(norm.data.quantiles) <- raw.data[,1]
> colnames(norm.data.quantiles) <- colnames(raw.data2)
> norm.data.quantiles
C1860gu C1775gu C1777gu
AA278251 164.8775 106.1608 210.4736
AA401404 369.8927 369.8927 350.9804
AA454191 106.1608 164.8775 106.1608
AA460836 350.9804 350.9804 369.8927
AA723761 421.3972 421.3972 395.6848
AA902654 395.6848 395.6848 421.3972
AA905415 210.4736 210.4736 164.8775
>
I think that there are a more sophisticated and more elegant way for
to do
this one!
>From here you can use limma, or maanova, or samr, or other package
that you
prefer.
I hope this help you.
--
Marcelo Luiz de Laia
Jaboticabal - SP - Brazil
sip:marcelolaia@ekiga.net <sip%3amarcelolaia@ekiga.net>
"Você vê as coisas como elas são e pergunta: por quê? Mas eu sonho com
coisas que nunca foram e pergunto: por que não? " - Bernard Shaw
[[alternative HTML version deleted]]
2008/5/8 Dozmorov, Mikhail G. (HSC) <mikhail-dozmorov at="" ouhsc.edu="">:
> We receive microarray data from processing facility in a simple
format o
> background subtracted intensities, here's an example, tab delimited:
>
> Gene ID C1860gu C1775gu C1777gu
> AA278251 100.825641 82.30144928 222.4144928
> AA401404 383.6702703 374.1666667 342.3405797
> AA454191 100.7403727 175.2884199 135.4404762
> AA460836 343.9164875 366.684058 351.8411658
> AA723761 445.059587 451.999359 355.5185897
> AA902654 400.1301282 431.4055556 367.1327381
> AA905415 200.9855072 208.0207576 218.5183983
>
> Thus, for each array (C2860gu,...) we have corresponding gene
expression
> data. How to import this data into ESET object for further handling?
?ExpressionSet is helpful. It will lead you in the following
direction (try to ensure your file--here named data.txt--is free of
extraneous white space since this may cause read.delim to interpret
numerical data as character):
library(Biobase)
exp <- new("ExpressionSet", exprs=as.matrix(read.delim("c:/data.txt",
row.names=1)))
# that's all that is required to accomplish what you wanted, but here
I will create
# some fictitious and random pheno data to illustrate adding pheno
data:
pheno <- matrix(runif(12, 1, 10), nrow=3)
# note that nrow(pheno) == ncol(exprs(eset)), as it must.
rownames(pheno) <- colnames(exprs(exp)); colnames(pheno) <- c("WBC",
"HgB", "AFP", "Age")
pheno <- new("AnnotatedDataFrame", data=as.data.frame(pheno))
exp <- new("ExpressionSet", exprs=as.matrix(read.delim("c:/data.txt",
row.names=1)), phenoData=pheno)
# let's check our work
pData(exp)
WBC HgB AFP Age
C1860gu 6.934886 7.284751 2.676714 8.815719
C1775gu 8.744655 7.067929 4.415327 7.904734
C1777gu 2.271367 4.686928 3.211371 6.035077
exprs(exp)
C1860gu C1775gu C1777gu
AA278251 100.8256 82.30145 222.4145
AA401404 383.6703 374.16667 342.3406
AA454191 100.7404 175.28842 135.4405
AA460836 343.9165 366.68406 351.8412
AA723761 445.0596 451.99936 355.5186
AA902654 400.1301 431.40556 367.1327
AA905415 200.9855 208.02076 218.5184
Cheers,
Eric
> Thank you!
>
>
>
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