Skip to content

Latest commit

 

History

History
188 lines (140 loc) · 9.01 KB

usage.md

File metadata and controls

188 lines (140 loc) · 9.01 KB

lehtiolab/nf-deqms: Usage

Table of contents

General Nextflow info

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 lehtiolab/nf-deqms --proteins proteins.txt --peptides peptides.txt --genes genes.txt --ensg ensg.txt --sampletable samples.txt -profile standard,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
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 lehtiolab/nf-deqms

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 lehtiolab/nf-deqms releases page and find the latest version number - numeric only (eg. 1.3.1). Then specify this when running the pipeline with -r (one hyphen) - eg. -r 1.3.1.

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. Profiles can give configuration presets for different compute environments. Note that multiple profiles can be loaded, for example: -profile standard,docker - the order of arguments is important!

  • standard
    • The default profile, used if -profile is not specified at all.
    • Runs locally and expects all software to be installed and available on the PATH.
  • docker
  • singularity
    • A generic configuration profile to be used with Singularity
    • Pulls software from singularity-hub
  • conda
    • A generic configuration profile to be used with conda
    • Pulls most software from Bioconda
  • awsbatch
    • A generic configuration profile to be used with AWS Batch.
  • test
    • A profile with a complete configuration for automated testing
    • Includes links to test data so needs no other parameters
  • none
    • No configuration at all. Useful if you want to build your own config from scratch and want to avoid loading in the default base config profile (not recommended).

--proteins, --peptides, --genes, --ensg

Use these to specify the location of your input tables (result tables from searches), e.g.:

--proteins "/path/to/data/proteins.txt" --genes "/path/to/data/genes.txt"

You are free to use another table that does not match the accession option, e.g. --peptides genes.txt, it will only be output under the wrong identifier (here "Gene names") in the QC then.

Differential expression analysis

DEqMS is used for DE analysis and it needs to know your sample group names. For this, you can pass a TSV file with sample names to --sampletable, it should contain a line for each channel/set combination with channel, set, sample, sample group e.g.:

126    setA   DMSO1  CTRL
127N   setA   ABC1   TREAT 
127C   setA   DMSO2  CTRL 
128N   setA   ABC2   TREAT
129N   setA   pool   X__POOL
...

For DE analysis, sample groups represent internal standard can be called X__POOL so they will be filtered out. Even when not using DEqMS you can provide a sample table for annotation of your quant output.

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 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.

AWS Batch specific parameters

Running the pipeline on AWS Batch requires a couple of specific parameters to be set according to your AWS Batch configuration. Please use the -awsbatch profile and then specify all of the following parameters.

--awsqueue

The JobQueue that you intend to use on AWS Batch.

--awsregion

The AWS region to run your job in. Default is set to eu-west-1 but can be adjusted to your needs.

Please make sure to also set the -w/--work-dir and --outdir parameters to a S3 storage bucket of your choice - you'll get an error message notifying you if you didn't.

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.

NB: Single hyphen (core Nextflow option)

-c

Specify the path to a specific config file (this is a core NextFlow command).

NB: Single hyphen (core Nextflow option)

Note - you can use this to override defaults. For example, you can specify a config file using -c that contains the following:

process.$multiqc.module = []

--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

--plaintext_email

Set to receive plain-text e-mails instead of HTML formatted.