Package: bacpage
AboutThis repository contains an easy-to-use pipeline for the assembly and analysis of bacterial genomes using ONT long-read or Illumina short-read technology.IntroductionAdvances in sequencing technology during the COVID-19 pandemic has led to massive increases in the generation of sequencing data. Many bioinformatics tools have been developed to analyze this data, but very few tools can be utilized by individuals without prior bioinformatics training.This pipeline was designed to encapsulate pre-existing tools to automate analysis of whole genome sequencing of bacteria. Installation is fast and straightfoward. The pipeline is easy to setup and contains rationale defaults, but is highly modular and configurable by more advance users.
A successful run generates consensus sequences, typing information, phylogenetic tree, and quality control report.FeaturesWe anticipate the pipeline will be able to perform the following functions:Reference-based assembly of Illumina paired-end readsDe novoassembly of Illumina paired-end readsDe novoassembly of ONT long readsRun quality control checksVariant calling usingbcftoolsMaximum-likelihood phylogenetic inference of processed samples and background dataset usingiqtreeMLST profiling and virulence factor detectionAntimicrobial resistance genes and plasmid detectionInstallationInstallminicondaby running the following two command:curl -L -O "https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-$(uname)-$(uname -m).sh"
bash Mambaforge-$(uname)-$(uname -m).shClone the repository:git clone https://github.com/CholGen/bacpage.gitInstall and activate the pipeline's conda environment:mamba env create -f environment.yaml
mamba activate bacpageTest the installation:snakemake --configfile test/test.yaml --all-temp --cores 8This command should run to completion without a problem. Please create an issue if this is not the case.UsageNavigate to the pipeline's directory.Copy theexample/directory to create a directory specifically for each batch of samples.cp example/ <your-project-directory-name>Place raw sequencing reads in theinput/directory of your project directory.Record the name and absolute path of raw sequencing reads in thesample_data.csvfound within your project directory.Replace the values<your-project-directory-name>and<sequencing-directory>inconfig.yamlfound within your project directory, with the absolute path of your project directory and pipeline directory, respectively.Determine how many cores are available on your computer:cat /proc/cpuinfo | grep processorFrom the pipeline's directory, run the entire pipeline on your samples using the following command:snakemake --configfile <your-project-directory-name>/config.yaml --cores <cores>This will generate a consensus sequence in FASTA format for each of your samples and place them in<your-project-directory-name>/results/consensus_sequences/<sample>.masked.fasta. An HTML report containing alignment and quality metrics for your samples can be found at<your-project-directory-name>/results/reports/qc_report.html. A phylogeny comparing your sequences to the background dataset can be found at<your-project-directory-name>/results/phylogeny/phylogeny.tree