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Same mutation in two different signatures #38
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Hi @rahulk87 |
Thanks @jayendrashinde91 for your prompt reply, I read the methods in paper. Actually, that's exactly my question is i.e. around 1000 mutations were attributed to signature SBS84 in sample X when I used mutations from specific genomic regions and when I used the whole genome mutations of that very sample, 0 mutations were attributed to SBS84, despite input contain those ~1000 mutations, how is it possible. This is the step before applying function "signature_origins". I used the object created by function "deconvolution_fit". Quite possible that I am missing something. |
Hi, Sorry for the late reply. The probability of a specific mutation being attributed to a given signature depends on the overall signature decomposition for the sample. So if you change the input (by selecting a subset of mutations), the proportion of signatures will change, which ultimately can modify the probability of a particular mutation being due to each process. Regarding why signature composition varies when you select only a subset of mutations, this can be explained by biological reasons (mutational processes are affected by various features including transcription or replication in a signature-dependent way) or technical reasons (e.g. the number of mutations considered is low and the signature less reliable). Hope this helps, |
Thanks Eric!! |
Hi,
I have been running Palimpsest on mutations in whole genome and same mutations but falling in specific regions of the genome. I observed that in these two different runs, same mutations annotated with two different signature i.e. mutation X annotated with signature SBS5 when I use whole genome mutations and same mutation X annotated with signature SBS84 when I use a subset of mutations in a specific genomic region.
Is there any plausible reason for this?
Thanks!!
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