A new web-deployed workflow of FLISOCHAR that only supports ONT long reads.
FLISOCHAR is a Florida BPHL Pipeline to genomically characterize bacterial isolates using a hybrid assembly method.
The pipeline flisochar_ontlr has the same functionality as flisochar_wf, but flisochar_ontlr only processes ONT long reads.
Flisochar-ontlr mainly aims to perform specifies identification of bacterial isolates using de novo assembly methods from Oxford Nanopore techonologies's long-read sequencing data. The pipeline is built in Nextflow, and Python is used to develop custom scripts, enabling the parse of output. It comes with singularity container to simplify installation.
The current worflow comprises:
- Quality Control
- De novo genome assembly
- Species Identification
- Genome Annotation
- Detection of Antimicrobial Resistance Genes
- Genomic Comparison
- Quality control on reads: fastp, longqc
- Three genome assemblers: canu, dragonflye, unicycler (run only canu and unicycler with pacbio long reads)
- Taxonomic classification progams: Kaiju. This version only emplements Kraken and Mash.
- Genome annotators: bakta, pgap, prokka (bakta is omitted in this version)
- Antimicrobial resistance genes marker: AMRFinderPlus
- Average nucleotide identity (ANI): pyANI(pgap)
At the moment, it is meant to clone this repository to your local directory.Clone a directory
Flisochar requires Python (version 3.6 or higher with the package Pandas installed), Nextlow, Singularity (apptainer) available in your system.
Currenly, the installation of pgap is also required. Before installing, we recommend to create a directory path for the installation under your group
mkdir /*/YourGroup/UserName/repos/ncbi/pgap
and cd to it. Set this environment variable <PGAP_INPUT_DIR> to the created path,
export PGAP_INPUT_DIR=/*/YourGroup/UserName/repos/ncbi/pgap/
simply to save everything on your HPC cluster. Note the slash at the end of the previous path(../pgap/) is required, so that all pgap's files are found in that directory. Download the pgap.py file as directed. Change the file into executable mode (chmod +x pgap.py). Then execute the command below on your terminal, and pagap installation will be complete.
./pgap.py --update -D apptainer
Before running flisochar_ontlr, ensure that required computing resources are available. Cores: 28, Memory: 180gb, Time ~ 2:00 hrs for one (long-read) bacterial sample
Once the pipeline is available on your system (or on HiPerGator), get an interactive run by following these first steps:
export PGAP_INPUT_DIR=/*/YourGroup/UserName/repos/ncbi/pgap/
module load nextflow apptainer
The above two commands and resources may also be written in a job scheduler (sbatch or slurm script) instead.
nextflow run flisochar_ontlr.nf --lreads '*.fastq.gz' --asb_tool <canu or unicycler or dragonflye > --genomeSize <numberm or numberM> --outdir 'output path'
The full usage may be accessed by executing the following command:
nextflow flisochar_ontlr.nf --help
Run the pipeline on the test dataset in your working directory using the following command:
nextflow run flisochar_ontlr.nf --lreads 'LRdata/*.fastq.gz' --asb_tool canu --genomeSize 3.5m --outdir flisochar_ontonlytest01
You may find ONT reads data from the flisochar page.
The flisochar_wf.nf worflow supports the maxikraken2 database if you want to use it to maximize Kraken percentages. However, users outside of the cluster HPG need to download maxikraken2 database from here. You will provide the path(where you downloaded the DB) and the name within the path (--kradb "/YOUR_PATH/kraken_databases" --krdbName "maxikraken2_1903_140GB" ) when use the maxikraken2 database.
Flisochar_wf ouputs seven directories refecting the worklow's features. (1) amrfinder,(2) ani_out, (3) annotation, (4) assemblies, (5) quality_control, (6) quast_out, and (7) species-identification