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nf-cmgg/preprocessing: Usage

Parameter documentation can be found here

Introduction

Samplesheet input

You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It can be a CSV (comma-separated values), TSV (tab-separated values), JSON (javascript object notation) or YAML (yet another markup language) file.

--input '[path to samplesheet file]'

The pipeline supports two types of samplesheets to be used as input: fastq and flowcell samplesheets. The type will be automatically detected and applied by the pipeline. The pipeline will also auto-detect whether a sample is single- or paired-end using the information provided in the samplesheet. The samplesheet can have as many columns as you desire.

Fastq samplesheet

A fastq samplesheet file consisting of paired-end data may look something like the one below.

- id: DNA1_L001
  samplename: DNA_paired1
  library: test_library
  genome: GRCh38
  aligner: bwamem
  markdup: bamsormadup
  umi_aware: false
  skip_trimming: false
  trim_front: 0
  trim_tail: 0
  adapter_R1: AGATCGGAAGAGCACACGTCTGAACTCCTTA
  adapter_R2: AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT
  run_coverage: true
  disable_picard_metrics: false
  roi: null
  tag: WES
  sample_type: DNA
  fastq_1: https://github.com/nf-cmgg/test-datasets/raw/preprocessing/data/genomics/homo_sapiens/illumina/fastq/sample1_R1.fastq.gz
  fastq_2: https://github.com/nf-cmgg/test-datasets/raw/preprocessing/data/genomics/homo_sapiens/illumina/fastq/sample1_R2.fastq.gz

Following table shows the fields that are used by the fastq samplesheet:

Column Description Required
id Unique sample identifier ✔️
samplename The sample name corresponding to the sample in the Fastq file(s) ✔️
genome The genome build to use for the analysis. Currently supports GRCh38, GRCm39 and GRCz11 ✔️ (unless organism is given)
organism Full name of the organism. Currently supports Homo sapiens, Mus musculus and Danio rerio ✔️ (unless genome is given)
library Sample library name ❌
tag The tag used by the sample. Can be one of WES, WGS, SeqCap and coPGT-M ❌
aligner The aligner to use for this sample. Can be one of these: bowtie2, bwamem, bwamem2, dragmap, strobe and snap. Set to false to output fastq. ✔️
markdup Markdup algorithm to use for duplicate marking. Can be set to bamsormadup, samtools or false ❌
umi_aware Whether UMI-aware processing should be used. Only applies when markdup is set to samtools ❌
skip_trimming Skip adapter trimming step ❌
trim_front Number of bases to trim from the front of reads ❌
trim_tail Number of bases to trim from the tail of reads ❌
adapter_R1 Adapter sequence for read 1 ❌
adapter_R2 Adapter sequence for read 2 ❌
run_coverage Run coverage analysis ❌
disable_picard_metrics Disable Picard metrics collection ❌
roi The path to a BED file containing Regions Of Interest for coverage analysis ❌
sample_type Sample type (e.g., DNA, RNA) ❌
fastq_1 FastQ file for reads 1 must be provided, cannot contain spaces and must have extension '.fq.gz' or '.fastq.gz' ✔️
fastq_2 FastQ file for reads 2 cannot contain spaces and must have extension '.fq.gz' or '.fastq.gz' ❌

An example samplesheet has been provided with the pipeline.

Flowcell samplesheet

A flowcell samplesheet file consisting of one sequencing run may look something like the one below.

- id: 200624_A00834_0183_BHMTFYDRXX
  samplesheet: https://github.com/nf-cmgg/test-datasets/raw/refs/heads/preprocessing/data/genomics/homo_sapiens/illumina/flowcell/SampleSheet_2.csv
  lane: 1
  flowcell: s3://test-data/genomics/homo_sapiens/illumina/bcl/
  sample_info: https://github.com/nf-cmgg/test-datasets/raw/refs/heads/preprocessing/data/genomics/homo_sapiens/illumina/flowcell/SampleInfo_2.json

Following table shows the fields that are used by the flowcell samplesheet:

Column Description Required
samplesheet Illumina flowcell for the flowcell lane ✔️
sample_info JSON/YML file with sample information. See the flowcell sample info documentation. ✔️
flowcell Illumina flowcell directory ✔️
lane Lane number ❌

An example samplesheet has been provided with the pipeline.

Flowcell sample info

A flowcell sample info JSON/YML file consisting for one sequencing run may look something like the one below.

- id: DNA1_L001
  samplename: DNA_paired1
  library: test_library
  genome: GRCh38
  aligner: bwamem
  markdup: bamsormadup
  umi_aware: false
  skip_trimming: false
  trim_front: 0
  trim_tail: 0
  adapter_R1: AGATCGGAAGAGCACACGTCTGAACTCCTTA
  adapter_R2: AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT
  run_coverage: true
  disable_picard_metrics: false
  roi: null
  tag: WES
  sample_type: DNA

Running the pipeline

The typical command for running the pipeline is as follows:

nextflow run nf-cmgg/preprocessing --input ./samplesheet.<csv|json|yaml> --outdir ./results -profile docker

This will launch the pipeline with the docker configuration profile. See below for more information about profiles.

Note that the pipeline will create the following files in your working directory:

work                # Directory containing the nextflow working files
<OUTDIR>            # Finished results in specified location (defined with --outdir)
.nextflow_log       # Log file from Nextflow
# Other nextflow hidden files, eg. history of pipeline runs and old logs.

If you wish to repeatedly use the same parameters for multiple runs, rather than specifying each flag in the command, you can specify these in a params file.

Pipeline settings can be provided in a yaml or json file via -params-file <file>.

:::warning Do not use -c <file> to specify parameters as this will result in errors. Custom config files specified with -c must only be used for tuning process resource specifications, other infrastructural tweaks (such as output directories), or module arguments (args). :::

The above pipeline run specified with a params file in yaml format:

nextflow run nf-cmgg/preprocessing -profile docker -params-file params.yaml

with params.yaml containing:

input: './samplesheet.csv'
outdir: './results/'
<...>

You can also generate such YAML/JSON files via nf-core/launch.

Updating the pipeline

When you run the above command, Nextflow automatically pulls the pipeline code from GitHub and stores it as a cached version. When running the pipeline after this, it will always use the cached version if available - even if the pipeline has been updated since. To make sure that you're running the latest version of the pipeline, make sure that you regularly update the cached version of the pipeline:

nextflow pull nf-cmgg/preprocessing

Reproducibility

It is a good idea to specify a pipeline version when running the pipeline on your data. This ensures that a specific version of the pipeline code and software are used when you run your pipeline. If you keep using the same tag, you'll be running the same version of the pipeline, even if there have been changes to the code since.

First, go to the nf-cmgg/preprocessing releases page and find the latest pipeline version - numeric only (eg. 1.3.1). Then specify this when running the pipeline with -r (one hyphen) - eg. -r 1.3.1. Of course, you can switch to another version by changing the number after the -r flag.

This version number will be logged in reports when you run the pipeline, so that you'll know what you used when you look back in the future. For example, at the bottom of the MultiQC reports.

To further assist in reproducibility, you can use share and re-use parameter files to repeat pipeline runs with the same settings without having to write out a command with every single parameter.

:::tip If you wish to share such profile (such as upload as supplementary material for academic publications), make sure to NOT include cluster specific paths to files, nor institutional specific profiles. :::

Core Nextflow arguments

:::note These options are part of Nextflow and use a single hyphen (pipeline parameters use a double-hyphen). :::

-profile

Use this parameter to choose a configuration profile. Profiles can give configuration presets for different compute environments.

Several generic profiles are bundled with the pipeline which instruct the pipeline to use software packaged using different methods (Docker, Singularity, Podman, Shifter, Charliecloud, Apptainer) - see below.

The pipeline also dynamically loads configurations from https://github.com/nf-core/configs when it runs, making multiple config profiles for various institutional clusters available at run time. For more information and to see if your system is available in these configs please see the nf-core/configs documentation.

Note that multiple profiles can be loaded, for example: -profile test,docker - the order of arguments is important! They are loaded in sequence, so later profiles can overwrite earlier profiles.

If -profile is not specified, the pipeline will run locally and expect all software to be installed and available on the PATH. This is not recommended, since it can lead to different results on different machines dependent on the computer environment.

  • debug
    • A generic profile with settings to help with debugging the pipeline. It will use more verbose logging.
  • arm64
    • A generic profile with settings to run the pipeline on ARM64 architecture machines (eg. Apple Silicon). It will use software containers built for ARM64 where available.
  • emulate_amd64
    • A generic profile with settings to run the pipeline on ARM64 architecture machines (eg. Apple Silicon) using AMD64 software containers. This is for when ARM64 containers are not available but you still want to run the pipeline on an ARM64 machine. Note that this will be slower than using ARM64 containers.
  • test
    • A profile with a complete configuration for automated testing
    • Includes links to test data so needs no other parameters
  • docker
    • A generic configuration profile to be used with Docker
  • singularity
    • A generic configuration profile to be used with Singularity
  • podman
    • A generic configuration profile to be used with Podman
  • shifter
    • A generic configuration profile to be used with Shifter
  • charliecloud
    • A generic configuration profile to be used with Charliecloud
  • apptainer
    • A generic configuration profile to be used with Apptainer

-resume

Specify this when restarting a pipeline. Nextflow will use cached results from any pipeline steps where the inputs are the same, continuing from where it got to previously. For input to be considered the same, not only the names must be identical but the files' contents as well. For more info about this parameter, see this blog post.

You can also supply a run name to resume a specific run: -resume [run-name]. Use the nextflow log command to show previous run names.

-c

Specify the path to a specific config file (this is a core Nextflow command). See the nf-core website documentation for more information.

Custom configuration

Resource requests

Whilst the default requirements set within the pipeline will hopefully work for most people and with most input data, you may find that you want to customise the compute resources that the pipeline requests. Each step in the pipeline has a default set of requirements for number of CPUs, memory and time. For most of the steps in the pipeline, if the job exits with any of the error codes specified here it will automatically be resubmitted with higher requests (2 x original, then 3 x original). If it still fails after the third attempt then the pipeline execution is stopped.

To change the resource requests, please see the max resources and tuning workflow resources section of the nf-core website.

Custom Containers

In some cases you may wish to change which container a step of the pipeline uses for a particular tool. By default nf-core pipelines use containers and software from the biocontainers or bioconda projects. However in some cases the pipeline specified version may be out of date.

To use a different container from the default container specified in a pipeline, please see the updating tool versions section of the nf-core website.

Custom Tool Arguments

A pipeline might not always support every possible argument or option of a particular tool used in pipeline. Fortunately, nf-core pipelines provide some freedom to users to insert additional parameters that the pipeline does not include by default.

To learn how to provide additional arguments to a particular tool of the pipeline, please see the customising tool arguments section of the nf-core website.

nf-core/configs and nf-cmgg/configs

In most cases, you will only need to create a custom config as a one-off but if you and others within your organisation are likely to be running nf-cmgg pipelines regularly and need to use the same settings regularly it may be a good idea to request that your custom config file is uploaded to the nf-core/configs git repository. Before you do this please can you test that the config file works with your pipeline of choice using the -c parameter. You can then create a pull request to the nf-core/configs repository with the addition of your config file, associated documentation file (see examples in nf-core/configs/docs), and amending nfcore_custom.config to include your custom profile.

See the main Nextflow documentation for more information about creating your own configuration files.

If you have any questions or issues please send us a message on Slack on the #configs channel.

Running in the background

Nextflow handles job submissions and supervises the running jobs. The Nextflow process must run until the pipeline is finished.

The Nextflow -bg flag launches Nextflow in the background, detached from your terminal so that the workflow does not stop if you log out of your session. The logs are saved to a file.

Alternatively, you can use screen / tmux or similar tool to create a detached session which you can log back into at a later time. Some HPC setups also allow you to run nextflow within a cluster job submitted to your job scheduler (from where it submits more jobs).

Nextflow memory requirements

In some cases, the Nextflow Java virtual machines can start to request a large amount of memory. We recommend adding the following line to your environment to limit this (typically in ~/.bashrc or ~./bash_profile):

NXF_OPTS='-Xms1g -Xmx4g'