Given two or more reads library sampled from their respective tissues (e.g. cancer or non-cancer), we have a method that can assign/classify the reads to their respective 'source genome', but without mapping to the reference genome.
This is inspired from the fact that there are no-identical genomes. Mapping them will lead to loss of information.
This method also considers error rates in the reads and coverage.
One possible application is to use it for finding rearrangement breakpoint reads.
What are the other potential application of such methods?
I would be interested to try this with some viral sequence reads, where a population may be a mixture of different clonal types with various mutations present. I am very interested in identifying breakpoints too.
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