22  The assembleBAC pipeline

Learning Objectives
  • Describe what the assembleBAC pipeline does.
  • Run a de novo assembly workflow from raw sequencing data.

22.1 Pipeline Overview

The assembleBAC pipeline

assembleBAC is a bioinformatics analysis pipeline written in Nextflow for assembling and annotating bacterial genomes. It also predicts the Sequence Type (ST) and provides QC metrics with Quast and CheckM2. It runs the following tools:

  • Shovill - de novo genome assembly
  • mlst - Sequence Type assignment
  • Bakta - annotation
  • Quast - assembly metrics
  • CheckM2 - assembly completeness
  • MultiQC - assembly metrics summary and pipeline information

See Course Software for a more detailed description of each tool.

Along with the outputs produced by the above tools, the pipeline produces the following summaries containing results for all samples run through the pipeline (found in the metadata directory):

  • checkm2_summary.tsv - final summary of CheckM2 statistics for input files in TSV format
  • transposed_report.tsv - final summary of Quast summary statistics for input files in TSV format
  • MLST_summary.tsv - final summary of Sequence Type assignments in TSV format

22.2 Prepare a samplesheet

As with bacQC and bactmap, we need to prepare a CSV file containing the information about our sequencing files, which will be used as an input to the assembleBAC pipeline. Refer back to the bacQC pipeline page for how to do this.

22.3 Running assembleBAC

Now that we have the samplesheet, we can run the assembleBAC pipeline. There are many options that can be used to customise the pipeline, but a typical command is shown below:

nextflow run avantonder/assembleBAC \
  -r main \
  -profile singularity \
  --max_memory '16.GB' --max_cpus 8 \
  --input SAMPLESHEET \
  --outdir results/assemblebac \
  --baktadb databases/bakta_light_20240119 \
  --genome_size GENOME_SIZE \
  --checkm2db databases/checkme2/uniref100.KO.1.dmnd
  • -r - tells Nextflow to pull the main version of assembleBAC from Github
  • -profile singularity - indicates we want to use the Singularity program to manage all the software required by the pipeline (another option is to use docker). See Data & Setup for details about their installation.
  • --max_memory and --max_cpus - sets the available RAM memory and CPUs. You can check this with the commands free -h and nproc --all, respectively.
  • --input - the samplesheet with the input files, as explained above.
  • --outdir - the output directory for the results.
  • --baktadb - the path to the directory containing the Bakta database files.
  • --genome_size - estimated size of the genome - Shovill uses this value to calculate the genome coverage.
  • --checkm2db - the path to the diamond file required by CheckM2.
Remember to QC your sequencing reads

Remember, the first step of any analysis of a new sequence dataset is to perform Quality Control. For the purposes of time, we’ve run bacQC for you and the results are in preprocessed/bacqc. Before you run assembleBAC, have a look at the read stats and species composition TSV files and make sure that the data looks good before we go ahead and assemble it.

Exercise 1 - Exercise: Running assembleBAC

Your next task is to run the assembleBAC pipeline on your data. Make sure you start this exercise from the S_aureus directory.

  • If you haven’t done so already, make sure to create a samplesheet for your samples. This follows the same format as detailed for the bacQC pipeline, so you can use the same python script as shown in that section.

  • In the folder scripts (within your analysis directory) you will find a script named 01-run_assemblebac.sh. This script contains the code to run this pipeline. Edit this script, adjusting it to fit your input files and the estimated genome size of Staphylococcus aureus.

  • Activate the Nextflow software environment (mamba activate nextflow).

  • Run the script using bash scripts/01-run_assemblebac.sh.

If the script is running successfully it should start printing the progress of each job in the assembleBAC pipeline. This will take a little while to finish.

  • Do a web search to find what the aproximate genome size of S. aureus is.
  • Look at the pipeline help (nextflow run avantonder/assembleBAC -r main --help) to find out what the format should be to specify the genome size in megabase pairs.

The fixed script is:

#!/bin/bash

nextflow run avantonder/assembleBAC \
  -r main \
  -profile singularity \
  --max_memory '16.GB' --max_cpus 8 \
  --input samplesheet.csv \
  --outdir results/assemblebac \
  --baktadb databases/bakta_light_20240119 \
  --genome_size 2M \
  --checkm2db databases/checkm2_v2_20210323/uniref100.KO.1.dmnd

After activating the software environment, we ran the script as instructed using:

bash scripts/01-run_assemblebac.sh

While it was running it printed a message on the screen:

executor >  local (1), slurm (125)
[5b/76f045] process > ASSEMBLEBAC:INPUT_CHECK:SAMPLESHEET_CHECK (samplesheet.csv) [100%] 1 of 1 ✔
[e6/2ea670] process > ASSEMBLEBAC:SHOVILL (ERX3876931_ERR3864878_T1)              [100%] 30 of 30 ✔
[94/bcfb5b] process > ASSEMBLEBAC:MLST (ERX3876931_ERR3864878_T1)                 [100%] 30 of 30 ✔
[9c/f528af] process > ASSEMBLEBAC:MLST_PARSE                                      [100%] 1 of 1 ✔
[07/e7d6bf] process > ASSEMBLEBAC:BAKTA (ERX3876931_ERR3864878_T1)                [100%] 30 of 30 ✔
[7f/6e833a] process > ASSEMBLEBAC:CHECKM2 (ERX3876931_ERR3864878_T1)              [100%] 30 of 30 ✔
[dc/41e8df] process > ASSEMBLEBAC:CHECKM2_PARSE                                   [100%] 1 of 1 ✔
[80/9598f1] process > ASSEMBLEBAC:QUAST                                           [100%] 1 of 1 ✔
[b1/dded73] process > ASSEMBLEBAC:CUSTOM_DUMPSOFTWAREVERSIONS (1)                 [100%] 1 of 1 ✔
[80/f2d907] process > ASSEMBLEBAC:MULTIQC (1)                                     [100%] 1 of 1 ✔
-[avantonder/assembleBAC] Pipeline completed successfully-
Completed at: 16-Nov-2023 11:45:37
Duration    : 32m 24s
CPU hours   : 41.5
Succeeded   : 126

22.4 Summary

Key Points
  • The assembleBAC workflow performs de novo assembly of bacterial genomes.
  • In addition, it also:
    • Annotates the assembly.
    • Performs sequence typing (using PubMLST schemes).
    • Determines assembly completeness.
    • Collects several quality statistics into a report.
  • Running the assembleBAC workflow requires:
    • A samplesheet detailing the sample names and their respective FASTQ files.
    • Directories to databases used for gene annotation (for Bakta) and genome completeness (for CheckM2).
    • An approximate genome size.