[BioC] RNA degradation problem

[Matthew Hannah]

Fangxin,

Yes it looks like the data is less than ideal. The last chip certainly
looks dubious and should probably be repeated. I would definetely check
with the experimenter how the samples were harvested and process and
CONFIRM that they are true biological replicates. It's amazing how many
lab plant biologists see pooled samples from a bulk of plants grown at
the same time as biological replicates when they are clearly not.

Looking at the RNA-deg plot (and sample labels) I guess they could be
epidermis cells or cell layer versus bulk stem or the underlying stem
tissue. If the tissue preparation required for the different sample
types was significantly different then this is the most likely reason
for the similarities seen in the RNA-deg plot, eg: it would take much
longer to take epidermal peels then a stem section and so RNA
degradation could be higher. Or the extracts could have a different
composition and something (eg:sugars) may effect the RNA extraction
efficiency or quality. Alternatively labelling or hyb in different
batches could also lead to the same effect.

I find hist, RNA deg, AffyPLM and a simple RMA norm followed by
plot(as.data.frame(exprs(eset.rma))) can answer in most cases for why it
didn't work, or won't work - in the rare case when someone asks for QC
before rather than after they realise the data is strange ;-)

Cheers,
Matt


>>>>>>>>>>> previous >>>>>>>>>>
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