Question: Determine whether it is MSI (micro satellite instability) or not
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gravatar for Chirag Nepal
2.1 years ago by
Chirag Nepal2.2k
Copenhagen
Chirag Nepal2.2k wrote:

Hi all,

I used msisensors ( https://github.com/ding-lab/msisensor ) to predict micro satellite instability (MSI).

As an example this patient has 287 MSI events.

Total_Number_of_Sites Number_of_Somatic_Sites %

16424 287 1.75

What is the minimum accepted percentage to define whether sample is MSI or not.

thanks !!

msi msisensors • 930 views
ADD COMMENTlink modified 2.1 years ago by lvulliard60 • written 2.1 years ago by Chirag Nepal2.2k
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gravatar for egeulgen
2.1 years ago by
egeulgen980
Istanbul
egeulgen980 wrote:

I don't have any experience with MSIsensor. In our lab, we use MSIseq, which offers a decision tree model classifier. You can train a decision tree model or use the default one. It then classifies the tumor as "MSI-H" or "non-MSI-H".

Maybe this might help; from MSIseq's article: "Tumors in which ≥40% of the markers in a panel show somatic length mutations are generally termed MSI-high (MSI-H)19. Tumors in which no markers show length mutations are termed microsatellite stable (MSS). The remaining tumors are sometimes termed MSI-low (MSI-L). "

ADD COMMENTlink modified 2.1 years ago • written 2.1 years ago by egeulgen980
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gravatar for lvulliard
2.1 years ago by
lvulliard60
lvulliard60 wrote:

Hi!
According to the original paper the MSI status should be called based on a MSIsensor > 3.5. In the literature different cutoffs have been used: 4 (here and here), or even up to 10 (here and here) depending on the sensitivity/specificity trade-off of interest and the biological context. If you don't have any experimental data on which you can test your cutoff, I assume these values could be a good starting point.
HTH.

ADD COMMENTlink written 2.1 years ago by lvulliard60
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