nf-core/mhcquant
Identify and quantify MHC eluted peptides from mass spectrometry raw data
1.2.1
). The latest
stable release is
2.6.0
.
Usage
Table of contents
- Introduction
- Running the pipeline
- Updating the pipeline
- Reproducibility
- Main arguments
- [Mass Spectrometry Search](#Mass Spectrometry Search)
--peptide_min_length
--peptide_max_length
--fragment_mass_tolerance
--precursor_mass_tolerance
--fragment_bin_offset
--fdr_threshold
--fdr_level
--number_mods
--num_hits
--digest_mass_range
--pick_ms_levels
--centroided
--prec_charge
--digest_mass_range
--activation_method
--enzyme
--fixed_mods
--variable_mods
--spectrum_batch_size
- Optional binding predicion
- Optional variant translation
- Job Resources
- Automatic resubmission
- Custom resource requests
- AWS batch specific parameters
- Other command line parameters
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
):
Running the pipeline
The typical command for running the pipeline is as follows:
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:
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:
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 nf-core/mhcquant 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
--mzmls
Use this to specify the location of your input mzML files. For example:
Please note the following requirements:
- The path must be enclosed in quotes
- The path must have at least one
*
wildcard character
--fasta
If you prefer, you can specify the full path to your fasta input protein database when you run the pipeline:
-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
.
- The default profile, used if
docker
- A generic configuration profile to be used with Docker
- Pulls software from dockerhub:
nfcore/mhcquant
singularity
- A generic configuration profile to be used with Singularity
- Pulls software from singularity-hub
conda
binac
- A profile for the BinAC cluster at the University of Tübingen
- Pulls software from Docker Hub via Singularity
cfc
- A profile for the Core Facility Cluster (CFC) at QBiC Tübingen
- Pulls software from Docker Hub via Singularity
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).
- No configuration at all. Useful if you want to build your own config from scratch and want to avoid loading in the default
Mass Spectrometry Search
--peptide_min_length
Specify the minimum length of peptides considered after processing
--peptide_max_length
Specify the maximum length of peptides considered after processing
--fragment_mass_tolerance
Specify the fragment mass tolerance used for the comet database search. For High-Resolution instruments a fragment mass tolerance value of 0.02 is recommended. (See the Comet parameter documentation: eg. 0.02)
--precursor_mass_tolerance
Specify the precursor mass tolerance used for the comet database search. For High-Resolution instruments a precursor mass tolerance value of 5ppm is recommended. (eg. 5)
--fragment_bin_offset
Specify the fragment bin offset used for the comet database search. For High-Resolution instruments a fragment bin offset of 0 is recommended. (See the Comet parameter documentation: eg. 0)
--fdr_threshold
Specify the false discovery rate threshold at which peptide hits should be selected. (eg. 0.01)
--fdr_level
Specify the level at which the false discovery rate should be computed. ‘peptide-level-fdrs’ is recommended. (‘peptide-level-fdrs’, ‘psm-level-fdrs’, ‘protein-level-fdrs’)
--number_mods
Specify the maximum number of modifications that should be contained in a peptide sequence match. (eg. 3)
--num_hits
Specify the number of hits that should be reported for each spectrum. (eg. 1)
--digest_mass_range
Specify the mass range that peptides should fullfill to be considered for peptide spectrum matching. (eg. 800:2500)
--pick_ms_levels
If one ms level in the raw ms data is not centroided, specify the level here. (eg. 2)
--centroided
Choose whether the specified ms_level in pick_ms_levels is centroided or not. (“True”, “False”)
--prec_charge
Specifiy the precursor charge range that peptides should fullfill to be considered for peptide spectrum matching. (eg. “2:3”)
--activation method
Specify which fragmentation method was used in the MS acquisition (‘ALL’, ‘CID’, ‘ECD’, ‘ETD’, ‘PQD’, ‘HCD’, ‘IRMPD’)
--enzyme
Specify which enzymatic restriction should be applied (‘unspecific cleavage’, ‘Trypsin’, see OpenMS enzymes)
--fixed_mods
Specify which fixed modifications should be applied to the database search (eg. ” or ‘Carbamidomethyl (C)’, see OpenMS modifications)
--variable_mods
Specify which variable modifications should be applied to the database search (eg. ‘Oxidation (M)’, see OpenMS modifications)
--spectrum_batch_size
Size of Spectrum batch for Comet processing (Decrease/Increase depending on Memory Availability)
Optional binding prediction
--run_prediction
Set to ‘True’ or ‘False’ depending on whether binding predictions using the tool mhcflurry should be run. (Check whether your alleles are supported by mhcflurry)
--refine_fdr_on_predicted_subset
Set to ‘True’ or ‘False’ depending on whether binding predictions using the tool mhcflurry should be used to subset all PSMs not passing the q-value threshold. If specified the FDR will be refined using Percolator on the subset of predicted binders among all PSMs resulting in an increased identification rate. (Check whether your alleles are supported by mhcflurry)
--affinity_threshold_subset
Affinity threshold (nM) used to define binders for PSM subset selection in the fdr refinement procedure (eg. 500)
--alleles
Specify a .tsv file containing the alleles of your probes. (line separated)
Optional variant translation
--include_proteins_from_vcf
Set to ‘True’ or ‘False’ depending on whether variants should be translated to proteins and included into your fasta for database search.
--vcf
Specify a .vcf file containing the information about genomic variants.
--variant_annotation_style
Specify style of tool used for variant annotation - currently supported: “SNPEFF”, “VEP”, “ANNOVAR”
--variant_reference
Specify genomic reference used for variant annotation: “GRCH37”, “GRCH38”
--variant_indel_filter
Specify whether insertions and deletions should not be considered for variant translation
--variant_frameshift_filter
Specify whether frameshifts should not be considered for variant translation
--variant_snp_filter
Specify whether snps should not be considered for variant translation
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:
--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.