Is there a method as good/superior as GISTIC/JISTIC to detect cancer-driving copy number alterations?
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10.5 years ago
Avro ▴ 160

Hi everyone!

I am using GISTIC/JISTIC to detect cancer-driving copy number alterations in breast cancer. I have read both articles, and they make a lot of sense. Additionally, please correct me if I am wrong, I assume that since GISTIC comes from the Broad Institute and that JISTIC is an improvement over GISTIC, both must be in the "top 5" algorithms out there. However, I would greatly appreciate the opinion of the community. What do you think? I know that there is no perfect method. Ultimately, everything has to be tested in the lab. For example, in my preliminary results, I got a lot of deleted olfactory receptors, which is most likely not cancer-driving according to the Broad. This is based on a newer tool called MutSigCV (also from the Broad).

According to the original MutSigCV article, olfactory receptors (ORs) can show up as significant due to the heterogeneity in the mutational processes in cancer (authors' hypothesis)(Lawrence et al. "Mutational heterogeneity in cancer and the search for new cancer-associted genes", Nature, 2013). Certain genes, like ORs, can accumulate mutations faster than others, even if their biology is not potentially oncogenic. Therefore, assuming a uniform rate of background mutations/aberrations (GISTIC/JISTIC) is somewhat wrong, no?

Finally, what is the main difference between GISTIC1.0 and GISTIC2.0? Is GISTIC2.0 equal to JISTIC?

Thank you very much for your time.

JISTIC aCGH GISTIC • 3.1k views
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Hi Avro,

If you end up using JISTIC, would you please share your experience, on how you did it.

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