[R] How to normalize to a set of internal references

Matthias Kohl Matthias.Kohl at stamats.de
Mon Mar 2 05:44:00 CET 2009


you should better ask this question on the Bioconductor mailing list.
For qPCR normalisation strategies take a look at
http://www.gene-quantification.info/

Best,
Matthias

Waverley wrote:
> Thanks for the advice.  My question is more on how to do this?
>
> Let me use a biology gene analysis example to illustrate:
> In biology, there are always some house keeping genes which differ
> little even at pathological conditions.
>
> We know that at different batches, there are external factors affect
> the measurements.  For example, overall signal intensity might be
> different due to lab reagents.
> A simplified picture:
> Day 1:  Using control samples, I have measured #1 to #110 genes and get data.
> Day 2: Using disease samples, I have measured again #1 to #110 genes
> and get data.
>
> For those two data sets, I noticed the overall signal intensity in Day
> 1, for each gene, is more than Day 2.
> I know, from biological literature,  gene 101 to 110, are "house
> keeping" genes, should not change much between disease and control.
> My questions arise, technically, how do I use gene 101 to 110 values
> to adjust the signals of gene 1 to 100 such that the batch effect can
> be corrected.  The differences revealing from the comparative analysis
> of 1 ~ 100 genes between disease and control are due to biology rather
> than lab artifacts.
>
> So the question is how to do that mathematically? If I have only one
> house keeping gene, then I can divide every gene to that to normalize,
> then compare.  But now I have 10 genes which can be utilized for
> normalization.  I assume, the more reference genes to be  used, the
> better, under this context.
>
> Can you help again?
>
> Thanks much in advance.
>
>
> Waverley wrote:
>   
>> Hi,
>>
>> I have a question of the method as how to normalize the data sets
>> according to a set of the internal measurements.
>>
>> For example, I have performed two batches of experiments contrasting
>> two different conditions (positive versus negative conditions): one at
>> a time.
>>
>> 1. each experiment, I measure signals of variable v1 to v100. I want
>> to understand v1 to v100 change under these two contrasting conditions
>>
>> 2. Also I know different variables v101 to v1110, total of 10 of them,
>> although they are different from each other, but they would of the
>> same or similar values under these two contrasting conditions
>>
>> 3. How do I do the internal normalization?  How can I use the the
>> variable v101 to v110 values to normalize the measures of v1 to v100
>> at either positive or negative condition to minimize batch effect?  I
>> hope the comparisons of values (v1 to v100) between two different
>> conditions can be more accurate and robust to external noises.
>>
>> In general, I have a couple of matrices of the same dimensions and a
>> reference matrix of values to be used as reference values to be
>> normalize to.  How should I do that?
>>
>>     
>
> I don't understand your problem well, but in general internal
> normalization is by and large an attempt to avoid appropriate modeling
> (e.g., incorporating block effects or certain covariates in a regression
> model), and results in overstated confidence of the final estimates by
> not taking into account the imprecision in the normalizing factors.
>
> Frank
>   

-- 
Dr. Matthias Kohl
www.stamats.de




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