Low percentage of classified reads (~18%) after Kraken2 analysis – is this expected?

Question

[sumah.1si21bt017]

Hello,

I am working with shotgun metagenomic data from rhizospheric soil samples. I preprocessed the data by removing low-quality reads and adapters. I also removed human genome contamination (only ~0.08% of reads were filtered out).

For taxonomic classification, I used Kraken2 with a custom database that I built from all NCBI organisms. The database size was ~1.5 TB, so I expected it to be quite comprehensive.

After running Kraken2 on the preprocessed and human-filtered reads, I observed that only ~18% of the reads were classified, while ~82% remained unclassified.

My questions are:

Is it normal to get such a low percentage of classified reads in soil metagenomic data?

Could there be an issue with my database construction or the way I ran Kraken2?

What are the possible reasons why ~80% of my reads remain unclassified despite using a large, comprehensive database?

Any advice, possible explanations, or shared experiences with similar soil metagenomic datasets would be greatly appreciated.

Thanks!

[dthorbur]

Hard to tell since we don't know how you actually constructed your database or what's actually in it. I would suggest trying using the standard database Kraken2 is distributed with. If the results are significantly higher classification, then it suggests something went wrong during your database creation.

[GenoMax]

why ~80% of my reads remain unclassified

Have you taken some of those reads and done some blast+ searches via the web interface to see if they return logical hits.

I used Kraken2 with a custom database that I built from all NCBI organisms.

What sequences did you use? Genomes from refseq,nt/nr or something else?