Introduction Usage Output Results

Introduction

This document describes the output produced by the pipeline.

The directories listed below will be created in the results directory after the pipeline has finished. All paths are relative to the top-level results directory.

Pipeline overview

The pipeline performs functional annotation and metabolic modeling of bacterial genomes using the following steps:

The pipeline performs functional annotation and metabolic modeling of bacterial genomes using the following steps:

  • Annotation - Genome annotation with Prokka or Bakta
  • MacSyFinder - Detection of macromolecular systems (secretion systems)
  • TRAITAR - Phenotype prediction from protein sequences
  • CarveMe - Genome-scale metabolic model reconstruction
  • Gapseq - Pathway analysis and metabolic modeling
  • Summary Table - Aggregated results from all tools
  • Pipeline information - Report metrics generated during the workflow execution

Annotation

Output files
  • annotation/
    • *.gff: Genome annotation in GFF3 format
    • *.faa: Predicted protein sequences
    • *.fna: Nucleotide sequences of predicted genes

Genomes are annotated using either Prokka (default) or Bakta. The annotation provides gene predictions and functional assignments.

MacSyFinder

Output files
  • macsyfinder/
    • *_all_systems.tsv: Detected macromolecular systems

MacSyFinder detects macromolecular systems such as Type III, IV, and VI secretion systems (TXSS).

TRAITAR

Output files
  • traitar/
    • *_phenotype_predictions.tsv: Phenotype predictions with confidence scores

TRAITAR predicts phenotypic traits from protein sequences using machine learning models.

CarveMe

Output files
  • carveme/
    • *.xml: Genome-scale metabolic models in SBML format

CarveMe reconstructs genome-scale metabolic models that can be used for flux balance analysis.

Gapseq

Output files
  • gapseq/
    • *-all-Pathways.tbl: Pathway predictions
    • *-Transporter.tbl: Transporter predictions
    • *.RDS: R model objects for further analysis

Gapseq predicts metabolic pathways and creates gap-filled metabolic models.

Summary Table

Output files
  • summary/
    • bacmodel_summary.tsv: Aggregated results from all enabled tools

The summary table provides a comprehensive overview of all analysis results in a single TSV file.

Pipeline information

Output files
  • pipeline_info/
    • Reports generated by Nextflow: execution_report.html, execution_timeline.html, execution_trace.txt and pipeline_dag.dot/pipeline_dag.svg.
    • Reports generated by the pipeline: pipeline_report.html, pipeline_report.txt and software_versions.yml. The pipeline_report* files will only be present if the --email / --email_on_fail parameter’s are used when running the pipeline.
    • Reformatted samplesheet files used as input to the pipeline: samplesheet.valid.csv.
    • Parameters used by the pipeline run: params.json.

Nextflow provides excellent functionality for generating various reports relevant to the running and execution of the pipeline. This will allow you to troubleshoot errors with the running of the pipeline, and also provide you with other information such as launch commands, run times and resource usage.
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