Question: Denosing Mirna Microarray Data From Blood Samples
0
gravatar for khan
5.5 years ago by
khan100
Germany
khan100 wrote:

Hi all,

I have miRNA microarray data from from blood sample. after normalization I saw quite different expression patterns for the same type of cancer among different patients(which I would expect to see at least some consistent expression pattern).

I want to find hidden pattern inside of this data set. what is the best approach to denoise and find the pattern ? I applied different clustering and dimensionality reduction algorithms but I couldn't find robust pattern .

what are your suggestions?

ADD COMMENTlink modified 5.2 years ago by QVINTVS_FABIVS_MAXIMVS2.2k • written 5.5 years ago by khan100
0
gravatar for pld
5.2 years ago by
pld4.8k
United States
pld4.8k wrote:

You could try t test each probe to see if in the tumor set that probe is significantly different than your healthy set. You might not see more than a few probes meet this level. You could use machine learning approaches to try and extract more complex situations but that might be a harder argument to support initially and validate later.

It is possible that there simply isn't a pattern at the level you are looking, or at all. Any number of differences between your patients could be causing significant differences in miRNA expression. On the other hand there may not be any differences. A lack of an obvious pattern doesn't mean your signal to noise ratio is poor, it could just mean that there isn't any signal to begin with. If your samples were as closely matched as possible and you still don't find anything, this suggests there isn't anything.

ADD COMMENTlink written 5.2 years ago by pld4.8k
0
gravatar for QVINTVS_FABIVS_MAXIMVS
5.2 years ago by
USA SoCal
QVINTVS_FABIVS_MAXIMVS2.2k wrote:

Maybe you are being to liberal with plotting? Sometimes restricting your values and replotting them (heatmaps normalize by row) can bring out patterns. But it's important to note this alteration.

ADD COMMENTlink written 5.2 years ago by QVINTVS_FABIVS_MAXIMVS2.2k
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