Dear all,
I'm currently working on a fairly (6.6 Gb) Illumina MiSeq metagenome. I expect it to be a low-diversity system, with a single genome being over-represented in the whole dataset. Prior to assembly, thus, I'd like to identify and extract the reads contributing to the highest coverage and just assemble them together. Is there a way to perform it? I tried BBnorm, but it only normalizes reads to a standard value, and khmer is taking ages to just build the graph.
-MikeT
I'm currently working on a fairly (6.6 Gb) Illumina MiSeq metagenome. I expect it to be a low-diversity system, with a single genome being over-represented in the whole dataset. Prior to assembly, thus, I'd like to identify and extract the reads contributing to the highest coverage and just assemble them together. Is there a way to perform it? I tried BBnorm, but it only normalizes reads to a standard value, and khmer is taking ages to just build the graph.
-MikeT