Introduction Usage Output

nf-core/ExoSeq Usage

General Nextflow information

Nextflow handles job submissions on SLURM or other environments, and supervises running the jobs. Thus the Nextflow process must run until the pipeline is finished. We recommend that you put the process running in the background through screen / tmux or similar tool. Alternatively you can run nextflow within a cluster job submitted your job scheduler.

It is recommended to limit the Nextflow Java virtual machines memory. We recommend adding the following line to your environment (typically in ~/.bashrc or ~./bash_profile):

NXF_OPTS='-Xms1g -Xmx4g'

Running the pipeline

The typical command for running the pipeline is as follows:

nextflow run SciLifeLab/nfcore/ExoSeq --reads '*_R{1,2}.fastq.gz' --genome GRCh37 -profile docker

This will launch the pipeline with the docker configuration profile (Swedish UPPMAX users use -profile uppmax). 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
results         # Finished results (configurable, see below)
.nextflow_log    # Log file from Nextflow
# Other nextflow hidden files, eg. history of pipeline runs and old logs.

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-core/ExoSeq

Reproducibility

It’s 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 nfcore/ExoSeq releases page and find the latest version number - numeric only (eg. 0.8). Then specify this when running the pipeline with -r (one hyphen) - eg. -r 0.8.

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.

Main Arguments

-profile

Use this parameter to choose a configuration profile. Each profile is designed for a different compute environment - follow the links below to see instructions for running on that system. Available profiles are:

--reads

Use this to specify the location of your input FastQ files. For example:

--reads 'path/to/data/sample_*_{1,2}.fastq'

Please note the following requirements:

  1. The path must be enclosed in quotes
  2. The path must have at least one * wildcard character
  3. When using the pipeline with paired end data, the path must use {1,2} notation to specify read pairs.

If left unspecified, a default pattern is used: data/*{1,2}.fastq.gz

--singleEnd

By default, the pipeline expects paired-end data. If you have single-end data, you need to specify --singleEnd on the command line when you launch the pipeline. A normal glob pattern, enclosed in quotation marks, can then be used for --reads. For example:

--singleEnd --reads '*.fastq'

It is not possible to run a mixture of single-end and paired-end files in one run.

Alignment tool

By default, the pipeline uses BWA to align the raw FastQ reads to the reference genome. BWA-MEM is the latest and it’s generally recommended as it is faster and more accurate compared to the other available BWA algorithms.

Reference Genomes

The pipeline config files come bundled with paths to the illumina iGenomes reference index files. If you are running on UPPMAX, these should work without any additional configuration. If running on AWS, the configuration is set up to use the AWS-iGenomes resource.

--genome (using iGenomes)

There are 31 different species supported in the iGenomes references. To run the pipeline, you must specify which to use with the --genome flag.

You can find the keys to specify the genomes in the iGenomes config file. Common genomes that are supported are:

  • Human
    • --genome GRCh37

There are numerous others - check the config file for more.

Note that you can use the same configuration setup to save sets of reference files for your own use, even if they are not part of the iGenomes resource. See the Nextflow documentation for instructions on where to save such a file.

--bwa_index, --fasta, --gtf

If you prefer, you can specify the full path to your reference genome when you run the pipeline:

--bwa_index '[path to BWA index]' \
--fasta '[path to FastA reference]' \
--gtf '[path to GTF file]'

The minimum requirements are a FastA and GTF file. If these are provided and no others, then all other reference files will be automatically generated by the pipeline.

--saveReference

Supply this parameter to save any generated reference genome files to your results folder. These can then be used for future pipeline runs, reducing processing times.

--saveTrimmed

By default, trimmed FastQ files will not be saved to the results directory. Specify this flag (or set to true in your config file) to copy these files when complete.

--saveAlignedIntermediates

As above, by default intermediate BAM files from the alignment will not be saved. The final BAM files created after the Picard MarkDuplicates step are always saved. Set to true to also copy out BAM files from BWA and sorting steps.

Adapter Trimming

If specific additional trimming is required (for example, from additional tags), you can use any of the following command line parameters. These affect the command used to launch TrimGalore!

--clip_r1 [int]

Instructs Trim Galore to remove bp from the 5’ end of read 1 (or single-end reads).

--clip_r2 [int]

Instructs Trim Galore to remove bp from the 5’ end of read 2 (paired-end reads only).

--three_prime_clip_r1 [int]

Instructs Trim Galore to remove bp from the 3’ end of read 1 AFTER adapter/quality trimming has been performed.

--three_prime_clip_r2 [int]

Instructs Trim Galore to remove bp from the 3’ end of read 2 AFTER adapter/quality trimming has been performed.

Capture Kits

Job Resources

Automatic resubmission

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 on UPPMAX with an error code of 143 (exceeded requested resources) it will automatically resubmit with higher requests (2 x original, then 3 x original). If it still fails after three times then the pipeline is stopped.

Custom resource requests

Wherever process-specific requirements are set in the pipeline, the default value can be changed by creating a custom config file. See the files in conf for examples.

Other command line parameters

--outdir

The output directory where the results will be saved.

--email

Set this parameter to your e-mail address to get a summary e-mail with details of the run sent to you when the workflow exits. If set in your user config file (~/.nextflow/config) then you don’t need to speicfy this on the command line for every run.

-name

Name for the pipeline run. If not specified, Nextflow will automatically generate a random mnemonic.

This is used in the MultiQC report (if not default) and in the summary HTML / e-mail (always).

NB: Single hyphen (core Nextflow option)

-resume

Specify this when restarting a pipeline. Nextflow will used cached results from any pipeline steps where the inputs are the same, continuing from where it got to previously.

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). Useful if using different UPPMAX projects or different sets of reference genomes.

--max_memory

Use to set a top-limit for the default memory requirement for each process. Should be a string in the format integer-unit. eg. `—max_memory ‘8.GB’“

--max_time

Use to set a top-limit for the default time requirement for each process. Should be a string in the format integer-unit. eg. --max_time '2.h'

--max_cpus

Use to set a top-limit for the default CPU requirement for each process. Should be a string in the format integer-unit. eg. --max_cpus 1

--multiqc_config

If you would like to supply a custom config file to MultiQC, you can specify a path with --multiqc_config. This is used instead of the config file specific to the pipeline.
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