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Old 01-14-2020, 06:31 AM   #2
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Location: Vienna

Join Date: Oct 2011
Posts: 123

For solid tissue analysis, you have the assumption, that your observed xNA (miroRNA, RNA, DNA, etc.) is derived from one origin showing a certain 'fingerprint'. Meaning that your observation is depending on the tissue type. In such a case, you can use e.g. datasets to perform a GSEA to obtain/rank the tissues which fit best to your data set.

In your blood or other liquid sample, you have a mixture of xNAs produced in various tissues. The "simple" dependency assumption is not working.
I fear it's not as easy to trace back from which tissue a certain amount a feature is produced. Especially, since you cannot deduce directly from an observed tissue-related expression/feature that this tissue is able to secrete the xNA into the blood.

There might be certain microRNAs / RNAs which are only produced in certain tissue(s) exclusively (for instance MUP4 in mouse lacrimal glands).

You might start with a simple likelihood model for each feature from which tissue it might came from.


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