Skip to content

Latest commit

 

History

History
97 lines (72 loc) · 4.78 KB

README.md

File metadata and controls

97 lines (72 loc) · 4.78 KB

flisochar_wf

A new web-deployed workflow of FLISOCHAR that supports both ONT and PacBio long reads

FLISOCHAR is a Florida BPHL Pipeline to genomically characterize bacterial isolates using a hybrid assembly method.

Introduction

Flisochar owes its inspiration to FLAQ-AMR, the Florida BPHL's standard pipeline for taxonomic characterization and AMR detection.

The Flisochar's overaching goal is to improve the identification of bacterial isolates using hybrid assembly from short and long-read sequencing data. Short-read and long-read sequences can be respectively from the Illumina MiSeq system and the Oxford Nanopore or Pacific BioSciences SMRT HiFi Technologies. 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.

Workflow

The current worflow comprises:

  1. Quality Control
  2. De novo genome assembly
  3. Species Identification
  4. Genome Annotation
  5. Detection of Antimicrobial Resistance Genes
  6. Genomic Comparison

Software Tools implemented

  1. Quality control on reads: fastp, longqc
  2. Three genome assemblers: canu, dragonflye, unicycler (run only canu and unicycler with pacbio long reads)
  3. Taxonomic classification progams: Kaiju. This version only emplements Kraken and Mash.
  4. Genome annotators: bakta, pgap, prokka (bakta is omitted in this version)
  5. Antimicrobial resistance genes marker: AMRFinderPlus
  6. Average nucleotide identity (ANI): pyANI(pgap)

Installation

At the moment, it is meant to clone this repository to your local directory.Clone a directory

Software Requirements

Flisochar requires Python (version 3.6 or higher with the package Pandas installed), Nextlow, Singularity (apptainer) available in your system.

Pgap

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

Resource Requirements

Before running flisochar, ensure that required computing resources are available. Cores: 28, Memory: 200gb, Time ~ 2:00 hrs for one hybrid (short-read, long-read) bacterial sample

Running Flisochar

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.

General Usage

nextflow run flisochar_wf.nf --lr_type <pcb or ont> --lreads '*.fastq.gz' --sreads '*_{1,2}.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_wf.nf --help

Example

Run the pipeline on the test dataset in your working directory using the following command:

nextflow run flisochar_wf.nf --lr_type pcb --lreads 'LRdata/*.fastq.gz' --sreads 'SRdata/*_{1,2}.fastq.gz' --asb_tool canu --genomeSize 3.5m --outdir flisochar_test01

Running with ONT data

You may find ONT reads data from the flisochar page.

Maxikraken2 Database

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 Ouput

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

Author: Tassy J-S. Bazile