Define where the pipeline should find input data and save output data.

Path to comma-separated file containing information about the samples in the experiment.

type: string
pattern: ^\S+\.csv$

You will need to create a design file with information about the samples in your experiment before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row. See usage docs.

The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.

required
type: string

Email address for completion summary.

type: string
pattern: ^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$

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 specify this on the command line for every run.

MultiQC report title. Printed as page header, used for filename if not otherwise specified.

type: string

Parameters used to describe centralised config profiles. These should not be edited.

Git commit id for Institutional configs.

hidden
type: string
default: master

Base directory for Institutional configs.

hidden
type: string
default: https://raw.githubusercontent.com/nf-core/configs/master

If you're running offline, Nextflow will not be able to fetch the institutional config files from the internet. If you don't need them, then this is not a problem. If you do need them, you should download the files from the repo and tell Nextflow where to find them with this parameter.

Institutional config name.

hidden
type: string

Institutional config description.

hidden
type: string

Institutional config contact information.

hidden
type: string

Institutional config URL link.

hidden
type: string

Set the top limit for requested resources for any single job.

Maximum number of CPUs that can be requested for any single job.

hidden
type: integer
default: 16

Use to set an upper-limit for the CPU requirement for each process. Should be an integer e.g. --max_cpus 1

Maximum amount of memory that can be requested for any single job.

hidden
type: string
default: 128.GB
pattern: ^\d+(\.\d+)?\.?\s*(K|M|G|T)?B$

Use to set an upper-limit for the memory requirement for each process. Should be a string in the format integer-unit e.g. --max_memory '8.GB'

Maximum amount of time that can be requested for any single job.

hidden
type: string
default: 240.h
pattern: ^(\d+\.?\s*(s|m|h|d|day)\s*)+$

Use to set an upper-limit for the time requirement for each process. Should be a string in the format integer-unit e.g. --max_time '2.h'

Less common options for the pipeline, typically set in a config file.

Display help text.

hidden
type: boolean

Display version and exit.

hidden
type: boolean

Method used to save pipeline results to output directory.

hidden
type: string

The Nextflow publishDir option specifies which intermediate files should be saved to the output directory. This option tells the pipeline what method should be used to move these files. See Nextflow docs for details.

Email address for completion summary, only when pipeline fails.

hidden
type: string
pattern: ^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$

An email address to send a summary email to when the pipeline is completed - ONLY sent if the pipeline does not exit successfully.

Send plain-text email instead of HTML.

hidden
type: boolean

File size limit when attaching MultiQC reports to summary emails.

hidden
type: string
default: 25.MB
pattern: ^\d+(\.\d+)?\.?\s*(K|M|G|T)?B$

Do not use coloured log outputs.

hidden
type: boolean

Incoming hook URL for messaging service

hidden
type: string

Incoming hook URL for messaging service. Currently, MS Teams and Slack are supported.

Custom config file to supply to MultiQC.

hidden
type: string

Custom logo file to supply to MultiQC. File name must also be set in the MultiQC config file

hidden
type: string

Custom MultiQC yaml file containing HTML including a methods description.

type: string

Boolean whether to validate parameters against the schema at runtime

hidden
type: boolean
default: true

Show all params when using --help

hidden
type: boolean

By default, parameters set as hidden in the schema are not shown on the command line when a user runs with --help. Specifying this option will tell the pipeline to show all parameters.

Validation of parameters fails when an unrecognised parameter is found.

hidden
type: boolean

By default, when an unrecognised parameter is found, it returns a warinig.

Validation of parameters in lenient more.

hidden
type: boolean

Allows string values that are parseable as numbers or booleans. For further information see JSONSchema docs.

Define pipeline options.

Required for downloading proteins from ncbi.

type: string

Required for downloading proteins from ncbi.

type: string

Minimum length of produced peptides.

type: integer
default: 9

Maximum length of produced peptides.

type: integer
default: 11

Only takes effect for pred_method 'syfpeithi'. Allow all peptide lengths within the range of min_pep_len to max_pep_len without reducing them to the matching allele models.

hidden
type: boolean

Epitope prediction method to use

type: string

Threshold for binder/non-binder calling when using SYFPEITHI epitope prediction method.

hidden
type: number
default: 0.5

Threshold for binder/non-binder calling when using MHCflurry or MHCnuggets epitope prediction methods. The default value of 0.426 corresponds to an IC50 of ≤500.

hidden
type: number
default: 0.426

Display supported alleles of all prediction methods and exit.

type: boolean

Prodigal mode, 'meta' or 'single'.

type: string
default: meta

Enables "deep" memory usage output for main DataFrames generated in pandas scripts ("deep" ensures accurate usage values, but slightly increases runtime).

hidden
type: boolean

Maximum chunk size (#peptides) for epitope prediction jobs.

type: integer
default: 4000000

Scaling factor for prediction_chunk_size parameter for usage in python scripts to reduce memory usage when handling DataFrames.

hidden
type: integer
default: 10

Maximum chunk size (#epitope predictions) for processing of downstream visualisations.

type: integer
default: 7500000

Number of files, which are merged in MERGE_PREDICTION_BUFFER

hidden
type: integer
default: 1000

Do not display mean comparison p-values in boxplots.

type: boolean