Suggested parameters for super-deeply (~2 billion reads) sequenced genomes?

[olgabot]

Hello! I'm following the suggested protocol for digital normalization on genomes. We are working on the Ixodes scapularis genome which is ~2GB in size, and is highly repetitive as found in previous drafts (PacBio on cell line, Illumina on tick embryos).

Given this genome and the sequencing depth, are the flags provided in the documentation (below) the "right" ones to use?

For high-coverage libraries (> ~50x), do three-pass digital normalization: run normalize-by-median.py with --cutoff=20 and then run filter-abund.py with --cutoff=2. Now split out the remaining paired-end/interleaved and single-end reads using extract-paired-reads.py, and run normalize-by-median.py on the paired-end and single-end files (using --unpaired-reads) with --cutoff=5.

For low-coverage libraries (< 50x) do single-pass digital normalization: run normalize-by-median.py to --cutoff=10.

Thank you!
Warmest,
Olga