Kmer Estimation – Kmergenie Tweaks on Geoduck Sequence Data

Earlier today, I ran kmergenie on our all of geoduck DNA sequencing data to see what it would spit out for an ideal kmer setting, which I would then use in another assembly attempt using SparseAssembler; just to see how the assembly might change.

The output from that kmergenie run suggested that the ideal kmer size exceeded the default maximum (k = 121), so I decided to run kmergenie a few more times, with some slight changes.

All jobs were run on our Mox HPC node.

Run 1

• Diploid

• Slurm script: 20180419_kmergenie_diploid_geoduck_slurm.sh

Run 2

• Diploid

• k 301

• Slurm script: 20180419_kmergenie_diploid_k301_geoduck_slurm.sh

Results:

Output folders:

• 20180419_kmergenie_diploid_geoduck/

• 20180419_kmergenie_diploid_k301_geoduck/

Slurm output files:

• 20180419_kmergenie_diploid_geoduck/slurm-162003.out

• 20180419_kmergenie_diploid_k301_geoduck/slurm-162004.out

Kmer histogram (HTML) reports:

• 20180419_kmergenie_diploid_geoduck/histograms_report.html

• 20180419_kmergenie_diploid_k301_geoduck/histograms_report.html

Diploid

Diploid, k 301

Okay, well, these graphs clearly show that the diploid setting is no good.

We should be getting a nice, smooth, concave curve.

Will try running again, without diploid setting and just increasing the max kmer size.