[BioC] liimma and Across Array Normalisation

[Gordon K Smyth]

On Sat, 8 Feb 2014, Saket Choudhary wrote:

> Hello Gordon,
>
> I had a chance to go through the paper. I have a set of negative and
> positive controls, arising out of single channel Genepix platform.
> From what I could gather, 'nec' method in limma performs
> backgroundcorrection using these negative control spots.

Yes, but the negative controls are assumed to behave exactly like probes 
for unexpressed genes.  This is true for Illumina Beadchips, but is often 
not the case for other platforms.  If not, then you would be better to 
stick with normexp as you are already using.

> However one of the inputs to 'nec' is also "detection.p", which the
> .gprs don't have.

detection.p is not a required argument.  It is used only when negative 
controls are not available.

> I could simply take a mean of all the negative controls E and Eb, and
> subtract it from each probe's E&Eb, doing it for all the arrays. Would
> this mimic what I want to acheive with the 'nec' function?

No, that naive approach is not equivalent and typically performs poorly.

Gordon

> Saket
>
> On 6 February 2014 13:04, Saket Choudhary <saketkc at gmail.com> wrote:
>> Hello Gordon,
>>
>> Unfortunately I do not have access to this as of now. I will however
>> get hold of it soon.
>>
>> After implementing this, I would expect the 'CONTROL' to have similar,
>> if not same values, right?
>>
>> However some of the values for these Control genes after the
>> normalisebetweenarray step have high variance. Is this behaviour
>> normal or am I missing something?
>>
>> Saket
>>
>> On 6 February 2014 06:32, Gordon K Smyth <smyth at wehi.edu.au> wrote:
>>> If 'x' is your background-corrected EList, then
>>>
>>>   w <- rep(1,nrow(x))
>>>   w[controls] <- 100
>>>   y <- normalizeBetweenArrays(x, method="cyclicloess", weights=w)
>>>
>>> does what you want.
>>>
>>> For an example of this approach:
>>>
>>>   http://rnajournal.cshlp.org/content/19/7/876
>>>
>>> Best wishes
>>> Gordon
>>>
>>> --------- original message ----------
>>> Saket Choudhary saketkc at gmail.com
>>> Thu Feb 6 06:59:42 CET 2014
>>>
>>> I am analysing a proteomics microarray data set for a two group
>>> sample(Normal and Disease) using single color channel. The arrays have a set
>>> of pre-defined CONTROL points whose expression levels are supposed to be
>>> similar/same across all the arrays.
>>>
>>> I would like to 'normalise' the levels of all probes such that normalisation
>>> ends up with all CONTROL points having similar expression levels. If I
>>> understand it right, normalizebetweenarray does not allow this kind of
>>> normalisation.
>>>
>>> Is there a pre-implemented function to do this? If not, what would be a way
>>> to acheive this kind of normalisation?
>>>
>>> Code: https://gist.github.com/saketkc/8669586
>>>
>>> ______________________________________________________________________
>>> The information in this email is confidential and intended solely for the
>>> addressee.
>>> You must not disclose, forward, print or use it without the permission of
>>> the sender.
>>> ______________________________________________________________________
>

______________________________________________________________________
The information in this email is confidential and intend...{{dropped:4}}