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 segmentation 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

Model to use for segmentation with stardist.

type: string

Number of tiles on the X axis for Stardist.

type: integer
default: 3

Number of tiles on the Y axis for Stardist.

type: integer
default: 3

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

Skip mindagap if your data does not contain gaps between tiles.

type: boolean

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$

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})$

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

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

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})$

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

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

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

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

Suffix to add to the trace report filename. Default is the date and time in the format yyyy-MM-dd_HH-mm-ss.

hidden
type: string