[BioC] using genomic DNA as universal reference

Jianping Jin jjin at email.unc.edu
Thu Jun 5 22:06:43 CEST 2008


Dear Juan,

Thanks for sharing your experience with me! It is helpful.

So when you are comparing data sets of interest that are collected from 
different experiments or at different time your assumption is that gDNA 
empirical distribution should be the same. The method, like 
"normalizeBetweenArrays" with method=Gquantile, can be applied to normalize 
all arrays. Is that correct?

best,

Jianping


--On Thursday, June 05, 2008 7:52 PM +0200 oliveros at cnb.csic.es wrote:

> Dear Jin,
>
> I used to work with this kind of data in the past: RNA in one channel and
> genomic DNA (gDNA) in the other. We used the gDNA as a reference value for
> each gene to quantify the amount of DNA present in each spot.
>
> I also noticed that the distribution of the intensities was different in
> both types of samples. In fact this is expectable as the amount of mRNA
> molecules in one sample has nothing to do with the amount of gDNA for the
> same gene in other sample.
>
> So I normalized the data separately:
>
> -I created two tables, one with all RNA values and other with all gDNA
> values.
>
> -I adjusted the quantiles of each table separately.
>
> -Then I calculated the ratio RNA intensity / gDNA intensity and I used
> this ratio RNA/gDNA as the expression value of the genes. In further
> analysis steps I treated them as data coming from single channel
> hybridizations.
>
>
> I hope that helps.
>
> best,
>
> Juan Carlos Oliveros
> Head of BioinfoGP Unit at CNB-CSIC
> Madrid, Spain
> http://bioinfogp.cnb.csic.es
>
>
>> Dear list,
>>
>> I would like to ask comments and suggestions on how to normalize
>> microarray
>> data with genomic DNA as reference.
>>
>> The experiments were performed with bacterial RNA and genomic DNA
>> samples. What I noticed was that the data were pretty consistent across
>> all chips on
>> both channels.  But there exists a huge difference between the two
>> channels
>> in terms of the distribution of the probe intensities, although the
>> average
>> intensities were the same for the both channels. T statistics with
>> non-normalized data showed that there were two thirds probes with p
>> values <= 0.05 by comparing the hybridization intensities between red
>> and green channels.
>>
>> Regarding to the huge difference described above the normalization
>> methods people usually use may not be appropriate for the RNA/DNA data
>> sets. What normalization algorithms would be useful if there is any?
>> Does anyone have experience with this?
>>
>> Any comments or suggestions will be appreciated!
>>
>> Jianping Jin
>>
>>
>> ##################################
>> Jianping Jin Ph.D.
>> Bioinformatics scientist
>> Center for Bioinformatics
>> Room 3133 Bioinformatics building
>> CB# 7104
>> University of Chapel Hill
>> Chapel Hill, NC 27599
>> Phone: (919)843-6105
>> FAX:   (919)843-3103
>> E-Mail: jjin at email.unc.edu
>>
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>
>



##################################
Jianping Jin Ph.D.
Bioinformatics scientist
Center for Bioinformatics
Room 3133 Bioinformatics building
CB# 7104
University of Chapel Hill
Chapel Hill, NC 27599
Phone: (919)843-6105
FAX:   (919)843-3103
E-Mail: jjin at email.unc.edu



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