Phip-seq TP vac Nextflow pipeline

Introduction

nf-core/phipseqtpvac is a bioinformatics pipeline designed to analyze Treponema pallidum PhiP-Seq assay data. It processes FASTQ files using a provided sample sheet, performing quality control (QC), trimming, and (pseudo-)alignment. The pipeline outputs a count matrix in CSV format, where rows represent features from the PhiP-Seq library and columns correspond to the input samples, providing a comprehensive quantification of feature counts across all samples.

1. Adapter and quality trimming (Cutadapt)
2. Pseudoalignment and quantification (Kallisto)
3. Aggregation of Kallisto quantifications into a unified count matrix (custom Python script)

Usage

[!NOTE] If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

csv sample,fastq_1,fastq_2 CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz

Each row corresponds to a single sample (one pull-down) with its associated pair of FASTQ files for paired-end sequencing. Example samplesheet can be found in the test_input directory along with the test data.

Now, you can run the pipeline using:

bash nextflow run nf-core/phipseqtpvac \ -profile <docker/singularity/...> \ --input example_samplesheet.csv \ --outdir <OUTDIR>

To run a specific verion of the pipeline, use the appropriate tag: nextflow run nf-core/phipseqtpvac -r <tag>

[!WARNING] Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

The pipeline parameters and their default values:

| Parameter | Description | Default value | | ------------- | ------------- | ------------- | | input | Path to the samplesheet with input data | Required | | outdir | Directory to save results | ./results | | cutadapt_minimum_len | Minimum read length after Cutadapt trimming | 20 | | trimR1 | Bases removed from the start of Forward reads (Cutadapt) | 44 | | trimR2 | Bases removed from the start of Reverse reads (Cutadapt) | 66 | | kal_index_ref | Path to the Kallisto index file | See latest release assets archive | | target_keys | Path to the PhiP-Seq library keys | See latest release assets archive |

kal_index_ref and target_keys files are provided in the assets archive of the latest release. The kal_index_ref file is a Kallisto index file for the PhiP-Seq library, and the target_keys file contains the PhiP-Seq library keys. The pipeline uses these files to quantify the PhiP-Seq library features.

Pipeline output

The pipeline generates separate nested output directories for results from Cutadapt, Kallisto, and the custom Kallisto output parsing program (cutadapt_out, kallisto_out, and parsed_raw_counts, respectively). Each directory contains the relevant quality control, trimming, or quantification files. A unified count matrix (parsed_raw_counts/kallisto_raw_counts_merged.csv) is produced, summarizing feature counts across all input samples.

Credits

nf-core/phipseqtpvac was originally written by @DariiaVyshenska.

We thank the following people for their extensive assistance in the development of this pipeline: Thaddeus Armstrong, Ben Wieland, Alex Greninger.

Contributions and Support

If you’re interested in contributing to this pipeline, please reach out to the repository owner.

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

You can cite the nf-core publication as follows:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.