[BioC] what to do with microarray outliers?

[Wei Shi]

Hi Theresa:

	Although it is possible that samples were wrongly labelled, I haven't encountered such a situation in all my microarray analyses in the last several years. What more happened was that arrays in the same experiment had variable qualities and in some rare circumstances some arrays could have a really poor quality due to for example sample preparation, hybridization problems and so on. In these cases however it would be better to keep these arrays in your analysis instead of throwing them away because these arrays could still provide useful information. But these arrays should be down weighted because their quality is poor. arrayWeights function is designed to address this problem. 

Cheers,
Wei


On Apr 13, 2011, at 2:04 PM, Jenny Drnevich wrote:

> Hi Theresa,
> 
> If you have two groups that are clearly separated on a PCA plot, except a couple samples are not in the "correct" group but instead in the other group, then I'd wager my pension* that these are mis-labeled samples, not outliers. I've seen this happen more than once, and while disturbing, we usually can never figure out exactly what happened. In general, outliers only refer to samples that are different from ALL others, not just samples that cluster with another group instead of their own.
> 
> HTH,
> Jenny
> 
> * I work for the state of Illinois, so my pension may not be worth much :(
> 
> At 11:06 PM 4/10/2011, Wei Shi wrote:
>> Hi Theresa:
>> 
>> Maybe you can try use array weights. See ?arrayWeights in limma for more details.
>> 
>> Cheers,
>> Wei
>> 
>> On Apr 10, 2011, at 9:56 PM, Theresa Brandt wrote:
>> 
>> > Hello,
>> >
>> >   I would like to ask what to do if there are outlying microarrays on PCA
>> > plot. Should I remove them from the further analysis or not?
>> >   I have two groups of samples and these groups are clearly separated on
>> > the PCA plot (first and second PC). But a few microarrays are not in the
>> > "correct" group.
>> >   What to do in a situation that one of the samples is much different from
>> > all the others (but technically it as a good microarray)? What would you do
>> > in such a situation?
>> >
>> > Sincerely,
>> > Theresa
>> >
>> >       [[alternative HTML version deleted]]
>> >
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