Determine whether it is MSI (micro satellite instability) or not
2
0
Entering edit mode
5.8 years ago
Chirag Nepal ★ 2.4k

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 • 2.1k views
ADD COMMENT
0
Entering edit mode
5.8 years ago
egeulgen ★ 1.3k

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 COMMENT
0
Entering edit mode
5.8 years ago
lvulliard ▴ 60

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 COMMENT

Login before adding your answer.

Traffic: 2510 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6