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|tsv)$

Path to a local or remote directory that is the “current working directory” for relative paths defined in the input samplesheet

type: string

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})$

Save intermediate amplicon reads generated from the raw input reads.

type: boolean

Trim N bases from the front of the reads

type: integer

Trim N bases from the tail of the reads

type: integer

The maximum length of a read

type: integer

The minimum length (bases) of a read

type: integer

The maximum number of Ns allowed in a read

type: integer

Minimum avg. quality a read must have (0 will disable the filter)

type: integer
default: 20

Remove duplicated reads (exact same sequence)

type: boolean

Remove PolyG sequences (length of 10 or more)

type: boolean

The number of mismatches allowed (in percentage) [default: 0.1; 0.0<=x<=0.9]

type: number
default: 0.1

Save intermediate QC read files containing all reads that passed the filters.

type: boolean

Save intermediate QC read files containing all reads that failed the filters.

type: boolean

The number of mismatches allowed (as a fraction)

type: number
default: 0.1

The minimum length of the barcode that must overlap when matching

type: integer

Save intermediate QC read files containing all reads that contain valid antibody barcodes.

type: boolean

Save intermediate QC read files containing all reads that failed the filters.

type: boolean

A list of comma separated antibodies to discard

type: string
pattern: (\S+)?(,\S+)*

The algorithm to use for collapsing (adjacency will perform error correction using the number of mismatches given)

type: string

The maximum number of neighbors to use when searching for similar sequences. This number depends on the sequence depth and the ratio of erroneous molecules expected. A high value can make the algorithm slower. This is only used when algorithm is set to ‘adjacency’

hidden
type: integer
default: 60

The number of mismatches allowed when collapsing (adjacency)

type: integer
default: 2

Discard molecules with with a count (reads) lower than this value

type: integer
default: 2

Use counts when collapsing (the difference in counts between two molecules must be more than double in order to be collapsed)

type: boolean

Save an intermediate parquet file containing collapsed read information.

type: boolean

Activate the multiplet recovery using leiden community detection

type: boolean
default: true

Number of iterations for the leiden algorithm, high values will decrease the variance of the results but increase the runtime [default: 10; 1<=x<=100]

hidden
type: integer
default: 10

Discard edges (pixels) with a count (reads) lower than this, use 1 to disable

hidden
type: integer
default: 2

Save an intermediate CSV file containing the unfiltered graph edge list.

type: boolean

Save an intermediate CSV file containing the recovered components after multiplet recovery.

type: boolean

The minimum size (pixels) a component/cell can have (disabled by default)

type: integer

The maximum size (pixels) a component/cell can have (disabled by default)

type: integer

Enable the estimation of dynamic size filters using a log-rank approach both: estimate both min and max size, min: estimate min size (—min-size), max: estimate max size (—max-size)

type: string

Enable aggregate calling, information on potential aggregates will be added to the output data

type: boolean
default: true

Save the raw_component_metrics.csv file from the annotate stage.

type: boolean

Save the PXL dataset after the annotate stage.

type: boolean

Skip analysis step

type: boolean

Compute polarization scores matrix (clusters by markers)

type: boolean
default: true

Compute colocalization scores (marker by marker) for each component

type: boolean
default: true

Use the bipartite graph instead of the one-node projection when computing polarization, coabundance and colocalization scores

type: boolean

Which transformation to use for the antibody counts when calculating polarity scores.

type: string

Set the number of permutations use to compute the empirical z- and p-values for the polarity score

type: integer
default: 50

The minimum number of counts of a marker to calculate the polarity score in the component

type: integer
default: 5

Select the type of transformation to use on the node by antibody counts matrix when computing colocalization

type: string

Select the size of the neighborhood to use when computing colocalization metrics on each component

type: integer
default: 1

Set the number of permutations use to compute the empirical p-value for the colocalization score

type: integer
default: 50

The minimum number of counts in a region for it to be considered valid for computing colocalization

type: integer
default: 5

The minimum number of counts in a component for it to be considered valid for computing colocalization

type: integer
default: 5

Save the PXL dataset after the analysis stage.

type: boolean

Skip layout step

type: boolean

Skip adding marker counts to the layout.

type: boolean

Select a layout algorithm to use. This can be specified as a comma separated list to compute multiple layouts. Possible values are: fruchterman_reingold, fruchterman_reingold_3d, kamada_kawai, kamada_kawai_3d, pmds, pmds_3d

type: string
default: wpmds_3d
pattern: (\S+)?(,\S+)*

Skip report generation

type: boolean

Global configuration options specific to nf-core/pixelator.

Override the container image reference to use for all steps using the pixelator command.

type: string

Save all intermediate results.

type: boolean

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

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

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$

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*)+$

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

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

Do not use coloured log outputs.

hidden
type: boolean

Incoming hook URL for messaging service

hidden
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

Validation of parameters fails when an unrecognised parameter is found.

hidden
type: boolean

Validation of parameters in lenient more.

hidden
type: boolean

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

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