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Hi everyone,
I have samples of viral genomes (wild samples). Each sample are possibly composed by dozens of structurally different genomes (in terms of indels, SNPs, inversions, transpositions, etc), and I have a reference genome of this virus.
I have 454 data from these samples, in which the reads have an average of 400 bp. I think that it'll be very hard (perhaps impossible) to determine which haplotype belongs to which individual genome in each sample (supported by the correct overlapping at the ends of the reads in a contig, in an stringent assembly)... Also, these viruses have several in tandem repeated regions, which beconme this assembly more complicated.
Is there any bioinformatics approach to reconstruct the most frequent structural variants from each sample, and also determine the presence or absent of specific haplotypes, without perform extra molecular cloning experiments?
Best!
I have samples of viral genomes (wild samples). Each sample are possibly composed by dozens of structurally different genomes (in terms of indels, SNPs, inversions, transpositions, etc), and I have a reference genome of this virus.
I have 454 data from these samples, in which the reads have an average of 400 bp. I think that it'll be very hard (perhaps impossible) to determine which haplotype belongs to which individual genome in each sample (supported by the correct overlapping at the ends of the reads in a contig, in an stringent assembly)... Also, these viruses have several in tandem repeated regions, which beconme this assembly more complicated.
Is there any bioinformatics approach to reconstruct the most frequent structural variants from each sample, and also determine the presence or absent of specific haplotypes, without perform extra molecular cloning experiments?
Best!
