nf-core pipeline · mycobacterium-tuberculosis, mycobacterium-tuberculosis-complex
nf-core/tbanalyzer
Bioinformatics pipeline for analysing members of the Mycobacterium tuberculosis complex.
What nf-core/tbanalyzer is
nf-core/tbanalyzer is a bioinformatics pipeline designed for the analysis of different members of the Mycobacterium tuberculosis complex (MTBC). The pipeline was originally written by @abhi18av within the nf-core community framework.
The software provides an automated workflow to process sequencing data from MTBC organisms, beginning with standardised sequence inspection and quality assessment across samples.
What the pipeline does
The pipeline takes sequencing data specified in a comma-separated samplesheet. The initial workflow executes read quality control via FastQC, after which the generated metrics are compiled into an aggregated quality control report using MultiQC.
Key facts
- Target organisms
- Mycobacterium tuberculosis complex
- Original author
- @abhi18av
- Read quality control
- FastQC
- Reporting tool
- MultiQC
- Input configuration
- CSV samplesheet
What you can use it for
- Raw read quality assessment
- Evaluating the sequencing quality of raw reads from Mycobacterium tuberculosis complex isolates using FastQC.
- Aggregated cohort QC reporting
- Compiling multi-sample quality control metrics and visualisations into unified MultiQC summary reports.
- Mycobacterium tuberculosis complex analysis
- Processing sequencing reads from diverse members of the Mycobacterium tuberculosis complex.
Run it here
The research agent runs nf-core/tbanalyzer with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
Strengths and limits
Good at
- Provides automated read-level quality evaluation using FastQC.
- Compiles multi-sample quality metrics into a single MultiQC report.
Watch out for
- Published documentation outlines initial quality control steps but does not detail further downstream analytical steps.
- Input sequencing data must be structured in a comma-separated samplesheet.
Questions
Can I run nf-core/tbanalyzer without my own cluster?
The research agent runs nf-core/tbanalyzer with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
What licence is nf-core/tbanalyzer under?
MIT, like every nf-core pipeline.
Which organisms are supported by the pipeline?
The pipeline is designed for members of the Mycobacterium tuberculosis complex.
How are inputs provided to nf-core/tbanalyzer?
Inputs are passed as a CSV samplesheet using the --input parameter, alongside an output directory specified by --outdir.
What tools handle quality control in the pipeline?
Raw read quality checks are carried out by FastQC, and the resulting metrics are summarised using MultiQC.
How to cite it
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
Written from nf-core/tbanalyzer's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.