Define where the pipeline should find input 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.

Test data as CSV file

type: string

the input file containing all input data

Experiment config as JSON format

type: string

the json config file that specifies all the parameters relative to the data manipulation.

Model file in Python

type: string

the model file in python, the model that will be tested by this pipeline.

Tuning config in yaml format

type: string

the config file with all the hyperparameter directives (choiches) and all ray tune specs.

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

type: string

The directory will contain a subdirectory with a name unique to each stimulus pipeline run.

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.

Files that can be provided as optional input or omitted.

File to be used to initialize the model in tuning

type: string

The initial weights of the model. These files can be used to start the training instead of random initialization. One can provide several files, each of them will be used for a different run.

Specify maximun processes resources

set maximum GPU limit

type: integer
default: 1

requesting the gpus for the tuning steps.

What to do and how to handle errors

Tells the pipeline how to behave on error

type: string
default: finish

refer to nextflow errorStrategy documentation for more details.

number of time to retry if err_strat is set to retry

type: integer

this also acts as a multiplier for recources request. If it failed for lack of resources it automaticly asks more the second time. take a look at test.conf for more details.

options to skip or change bhaviour of pipeline

checks if all input are comatible and the model can be tuned.

type: boolean
default: true

flag to tell whether to check or not if the model can be tuned and trained. It does one call of the batch function, (predicting), of the model importing and using everything needed for that. Default run such a check.

optional flag to do a more/less extensive check during check_model.

type: string

This will override user given num_sample value for the tune run. This will give the user control on how extensive it wants the check to be. by default is going to be set to 3.

run the shuffle sanity check

type: boolean
default: true

flag to tell wether to shuffle or not the data and run a train on it. Sanity check always run on default.

developer flag

type: boolean

flag used to switch to debug mode for the pipeline. more verbose outputs.

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

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

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

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.

Boolean whether to validate parameters against the schema at runtime

hidden
type: boolean
default: true

Base URL or local path to location of pipeline test dataset files

hidden
type: string
default: https://raw.githubusercontent.com/nf-core/test-datasets/