Can we do unsupervised clustering of Varscan output based on variant frequencies?
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10.0 years ago
ivivek_ngs ★ 5.2k

Dear All,

I have some queries regarding the Varscan output. I have some varscan output files where I am trying to understand two different kind of tumors, high and low grade and their corrsponding IPSC lines(induced pluripotent stem cells) derived from their corresponding tumors. I obtained the somatic mutations for tumors and IPS with the somatic caller of VarScan using normal/tumor and normal/IPS. The tumor somatic mutations were called at frequency of 5% with minimum var frequency of threshold and the IPS were called without any frequency threshold as it should obvious that the cell which is reprorammed to IPS should also contain the frequencies that are with high frequencies in tumor. My primary aim is to understand if the mutations in the tumor are passed on to the IPS or not. I am trying to establish that the reprogrammnig does not alter the genetic background of the IPSCs. I have noticed that same base which is mutated at a frequency of 30% in normal/tumor is mutated in IPSCs in (normal/IPSC) with a frequency of 40%. Which is not wrong right as am trying to understand in the IPSC which is a single cell reprogrammed where we count the freqency of the mutation of a SNP with respect to normal sample. Is it logical to now take account of the frequencies of these SNPs and create a matrix of all the frequencies from tumor and its IPS nad try to obtain a clustering or a correlation matrix to understand if the IPS are more inclined towards each other or to their tumor samples or not. Did anyone did any sort of correlation clustering of their different VarScan outputs for an experiment to understand the same? It would be nice if anyone can share some ideas.

Thanks

varscan2 next-gen exome-sequencing varscan • 2.5k views
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From your newer posts, I assume you were able to answer most of these questions. If not, please update the question with your latest understanding of the problem, and add keywords like cancer or ipsc, so relevant folks can find it.

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