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Please help....normalization by the median of some control genes

4 messages · David Lyon, Rui Barradas, arun +1 more

#
Can someone show me some code to do normalization by the median of some control genes for the example below?

Many Many Thanks in advance



This strategy selects a subset of genes (called ?control genes?) and makes the median of their data distribution similar across arrays.

??? ??? id1??? id2??? id3
control1??? 0.8??? 0.7??? 0.6
control2??? 0.6??? 0.2??? 0.4
probe1??? ??? 0.3??? 0.2??? 0.5
probe2??? ??? 0.4??? 0.9??? 0.7
probe3??? ??? 0.6??? 0.7??? 0.4
#
Hello,

I'm not sure I understand what you want. You want the medians to be 
"similar"? Why not equal?
(The code below assumes ids represent genes.)


d <- read.table(text="
         id1    id2    id3
control1    0.8    0.7    0.6
control2    0.6    0.2    0.4
probe1        0.3    0.2    0.5
probe2        0.4    0.9    0.7
probe3        0.6    0.7    0.4
", header=TRUE)
d

d.new <- sapply(d, function(x) x - median(x))

The medians are now all equal to zero.

Hope this helps,

Rui Barradas

Em 23-08-2012 13:37, David Lyon escreveu:
#
HI,

You could try:
limma package: normalizeWithinArrays()
A.K.



----- Original Message -----
From: David Lyon <david_lyon3 at yahoo.com>
To: "r-help at r-project.org" <r-help at r-project.org>
Cc: 
Sent: Thursday, August 23, 2012 8:37 AM
Subject: [R] Please help....normalization by the median of some control genes

Can someone show me some code to do normalization by the median of some control genes for the example below?

Many Many Thanks in advance



This strategy selects a subset of genes (called ?control genes?) and makes the median of their data distribution similar across arrays.

??? ??? id1??? id2??? id3
control1??? 0.8??? 0.7??? 0.6
control2??? 0.6??? 0.2??? 0.4
probe1??? ??? 0.3??? 0.2??? 0.5
probe2??? ??? 0.4??? 0.9??? 0.7
probe3??? ??? 0.6??? 0.7??? 0.4


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#
On 8/23/12 7:37 AM, "David Lyon" <david_lyon3 at yahoo.com> wrote:

            
??? ??? id1???  id2??? id3
control2??? 0.6??? 0.2??? 0.4
probe1??? ??0.3??? 0.2??? 0.5
probe2??? ??0.4??? 0.9??? 0.7
probe3??? ??0.6??? 0.7??? 0.4

SuperCurve* has a normalization function that normalizes
by median, variable slope, and housekeeping genes.
But it's geared towards slightly larger problems...
It's used in production by our Core Labs to process their RPPAs.

<http://bioinformatics.mdanderson.org/main/SuperCurve:Overview>

* Shameless plug