[BioC] RNA degradation problem

[fhong@salk.edu]

Hi Naomi,
Thank you for your help.

> It looks to me as if there is a problem in this experiment.  I cannot
> speak for the efficacy of the RNA degradation plot.  But unless a
> large amount of differential expression occurs in this experiment,
> the very close similarity between the duplicates compared to the
> other conditions leads me to thing that these duplicates were either
> not biological replicates, or the duplicates were processed together
> causing correlation.
 I know that the replicates are biological replicates, so I think very
likely that they processed the duplicates together ( will check with the
experimenter)  However, if this is the case, what we can do to? It
violates the assumption of Limma ? Maybe Rank product can be a solution
since it computes 4 ratios among duplicates from two conditions?


Many thanks!
fangxin


> I have seen this type of thing with spotted arrays when arrays
> processed in a single batch are much more similar than biological
> replicates processed on different days.
>
> --Naomi
>
> At 08:12 AM 1/18/2006, James W. MacDonald wrote:
>>fhong at salk.edu wrote:
>> > Dear list,
>> >
>> > I have this 8 affy arrays under 2*2 factorial design, with duplicates
>> > under each condition. The RNA degradation plot worries me since the
>> slopes
>> > from 8 arrays are so different, with duplicates under each condition
>> as
>> > one group (see the QC plots at http://cactus.salk.edu/temp/QC-1.jpeg)
>> > I would suspect that these arrays were processed  under different
>> levels
>> > if amplification.
>> >
>> > My problem is how to handle this data set beside doing the
>> normalization?
>> > Will this pattern seriously bias the result? I read some previous
>> message
>> > about this topic, just hope to get more information.
>>
>>I find that the RNA degradation plots are less useful for indicating
>>possible problems than the density plots. If the density plots are all
>>reasonably similar, in my experience the normalization should be fine.
>>Another excellent plot for detecting problems is the residual plot in
>>the affyPLM package.
>>
>>
>>Best,
>>
>>Jim
>>
>>
>> >
>> > Many thanks!
>> > Fangxin
>> >
>> >
>> > --------------------
>> > Fangxin Hong  Ph.D.
>> > Plant Biology Laboratory
>> > The Salk Institute
>> > 10010 N. Torrey Pines Rd.
>> > La Jolla, CA 92037
>> > E-mail: fhong at salk.edu
>> > (Phone): 858-453-4100 ext 1105
>> >
>> >
>> >
>> > --------------------
>> > Fangxin Hong  Ph.D.
>> > Plant Biology Laboratory
>> > The Salk Institute
>> > 10010 N. Torrey Pines Rd.
>> > La Jolla, CA 92037
>> > E-mail: fhong at salk.edu
>> > (Phone): 858-453-4100 ext 1105
>> >
>> > _______________________________________________
>> > Bioconductor mailing list
>> > Bioconductor at stat.math.ethz.ch
>> > https://stat.ethz.ch/mailman/listinfo/bioconductor
>>
>>
>>--
>>James W. MacDonald
>>Affymetrix and cDNA Microarray Core
>>University of Michigan Cancer Center
>>1500 E. Medical Center Drive
>>7410 CCGC
>>Ann Arbor MI 48109
>>734-647-5623
>>
>>_______________________________________________
>>Bioconductor mailing list
>>Bioconductor at stat.math.ethz.ch
>>https://stat.ethz.ch/mailman/listinfo/bioconductor
>
> Naomi S. Altman                                814-865-3791 (voice)
> Associate Professor
> Dept. of Statistics                              814-863-7114 (fax)
> Penn State University                         814-865-1348 (Statistics)
> University Park, PA 16802-2111
>
>
>


--------------------
Fangxin Hong  Ph.D.
Plant Biology Laboratory
The Salk Institute
10010 N. Torrey Pines Rd.
La Jolla, CA 92037
E-mail: fhong at salk.edu
(Phone): 858-453-4100 ext 1105