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  • Why is predicted best k for de novo assembly so different from actual best k?

    Greetings everyone,

    I’m doing my first genome assembly for a non-model plant species, and I need some insight about best kmer lengths for DBG-based assembly. My NGS data is a full lane of Illumina HiSeq V4 2x125 with a single library of insert size 350. Using kmer-counting methods, such as Jellyfish, my predicted best value k has ranged from 93-101 due to the large number of reads and their relatively-long length for HiSeq reads.

    However, I have found all of my highest-quality assemblies at kmer-lengths <40, with my highest N50 and CEGs-mapped occurring at lengths 29 and 33, respectively. Does anyone know why I’m seeing such a large difference between predicted best k and actual best k? Given that it’s a discrepancy of more than 50bp, I feel like there’s got to be a common explanation that googling simply hasn’t turned up. I predict it’s related to heterogeneity in the reads, but I’m unable to find much elaboration on the effect of heterogeneous reads, so thanks for any insights!

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