A community effort to collect a curated set of analysis pipelines built using Nextflow.

nf-core

Hi Team,
I have WGS data for _Streptococcus pneumoniae_ sequenced using the Oxford Nanopore SQK-RBK114.96 kit on a PromethION flowcell.
I'm looking for recommendations or a workflow to extract the following from my dataset:
• Species confirmation/identification
•  MLST (MultiLocus Sequence Typing)
•  Serotyping
•  AMR (Antimicrobial Resistance) gene detection
•  Virulence factor gene detection
Given that it's long-read Nanopore data with moderate coverage, what tools or pipelines would you recommend?

<@ULAQXBR19>
I used the following command to process the samples:

```bactopia -profile docker --ont "$file" --sample $(basename "$file" .fastq.gz) --species 'Streptococcus pneumoniae' --genome_size 2110968 --outdir outdir_300 --ont_minlength 300 --nanohq --dragonflye_assembler flye --coverage 25 --ont_minqual 10 --min_contig_len 0 --min_contig_cov 0 --max_cpus 36 --max_memory 64.GB```
• The assembled `.fna` files were used for serotyping with *Pathogenwatch* and *SeroBA*.
• However, there are some samples that could not be identified.
•  Is there any way to find out what went wrong?


Genome length after assembly of unidentified samples is less then S. pneumo (2.11MB)

Not sure without knowing more information. Perhaps some samples were not actually S. pneumo? Any indication from any other tools run, like kraken?

Sorry for the delayed response — I was waiting for another batch of samples to cross-check the issue. It turns out that the problem was due to DNA fragmentation during library preparation, which resulted in an N50 below 500. Additionally, there weren't enough reads to produce a reliable assembly.
Thank you so much for your recommendation — I really like the Bactopia pipeline. It's been very helpful.

kraken results shows more than 60% of reads were unclassified.