Define which segmentation methods should be used and how.

List of segmentation tools to apply to the image written as a comma separated string: mesmer,cellpose,ilastik would run all three options.

required
type: string
default: mesmer

Minimum area size (in pixels) for segmentation masks.

type: integer

Maximum area size (in pixels) for segmenation masks.

type: integer

Cell diameter, if 0 will use the diameter of the training labels used in the model, or with built-in model will estimate diameter for each image.

type: integer
default: 30

Specifies the channel to be segmented by Cellpose.

type: integer

Specifies nuclear channel index for Cellpose if using pretrained models such as cyto.

type: integer

Pretrained Cellpose model to be used for segmentation.

type: string
default: cyto

Custom Cellpose model can be provided by the user.

type: string

Flow error threshold for Cellpose.

type: number
default: 0.4

Should cells detected near image edges be excluded.

type: boolean
default: true

Should flow fields from Cellpose be saved?

hidden
type: boolean

Pixel size in microns for segmentation with Mesmer.

type: number
default: 0.138

Compartment to be segmented with Mesmer (nuclear, whole-cell)

type: string
default: whole-cell

Provide ilastik with a pixel classification project to produce probability maps.

type: string

Provide ilastik with a multicut project to create segmentation masks.

type: string

Defines gridsize for Mindagap and should contrast adjustment be applied and how.

Box size used by Mindagap to overcome gaps, a larger number allows to overcome large gaps, but results in less fine details in the filled grid.

type: integer
default: 3

Loop number performed by Mindagap. Lower values are faster, but the result is less good.

type: integer
default: 40

Contrast limit for localized changes in contrast by CLAHE.

type: number
default: 0.01

Number of histogram bins to be used by CLAHE.

type: integer
default: 256

Pixel size to be used by CLAHE.

type: number
default: 0.138

Kernel size to be used by CLAHE.

type: number
default: 25

Specifies whether contrast-limited adaptive histogram equalization should be skipped.

type: boolean

Tile size (distance between gridlines) for Mindagap.

hidden
type: integer
default: 2144

Should Mindagap blur area around grid for smoother transitions between tiles with different exposures.

hidden
type: boolean

Tile size used for pyramid generation (must be divisible by 16).

hidden
type: integer
default: 1072

Define whether a cropped training set for segmentation methods should be created.

Create subset for training a segmentation model.

type: boolean

Indicates crop size on x axis.

type: integer
default: 400

Indicates crop size on y axis.

type: integer
default: 400

Number of crops you would like to extract.

type: integer
default: 4

Indicates fraction of pixels per crop above global threshold to ensure tissue and not only background is selected.

type: number
default: 0.4

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.

required
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.

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

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