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|tsv|yml|yaml)$

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.

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.

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.

Save intermediate amplicon reads generated from the raw input reads.

type: boolean

Save intermediate amplicon reads generated from the raw input reads.

type: boolean

The number of mismatches allowed while anchoring reads using LBS sequences (in percentage of seen LBS length) [default: 0.1; 0.0<=x<=0.5]

type: number

Remove PolyG sequences (length of 10 or more)

type: boolean

Minimum average quality a read must have. Pass 0 to disable quality filtering.

type: integer
default: 20

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

Reads longer then given length will be trimmed to the given length. If you set this argument it will overrule the value from the chosen design

The minimum length (bases) of a read

type: integer

Reads shorter then given length will be discarded. If you set this argument it will overrule the value from the chosen design.

The maximum number of Ns allowed in a read

type: integer

The default value of 0 means any reads with N in it will be filtered out

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

If you set this argument it will overrule the value from the chosen design

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

The number of mismatches allowed in marker barcodes.

type: number
default: 1

The target number of reads in a single file of the partitioned demux output.

type: string
default: 50M

The maximum number of chunks that the demuxed ouput for each umi region will be split into

type: number
default: 8

The demux and collapsing strategy to use

type: string

Save intermediate parquet files containing embeddings of all reads that contain valid antibody barcodes.

type: boolean

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

type: boolean

Save intermediate FASTQC read files containing all reads that do not contain valid antibody barcodes.

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

Save an intermediate parquet file containing collapsed read information.

type: boolean

The algorithm to use for collapsing.

type: string

The number of mismatches allowed when collapsing (adjacency)

type: integer
default: 2

Save an intermediate parquet file containing collapsed read information.

type: boolean

Activate the multiplet recovery using leiden community detection

type: boolean
default: true

The number of times a component can be broken down into smaller components during the multiplet recovery process.

hidden
type: integer
default: 5

Maximum number of edges between the produced components as a result of a component split operation during the multiplet recovery process.

hidden
type: integer
default: 5

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

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.

type: string

Following options are available:

  • both: estimates both minimum and maximum component size
  • min: estimates the minimum component size (or uses {MINIMUM_N_EDGES_CELL_SIZE} edges, whichever is smallest)
  • max: estimates the maximum component size.

Note that this cannot be set at the same time as --min-size or --max-size.

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

Save the PXL dataset after the graph stage.

type: boolean

Activate the multiplet recovery using leiden community detection

type: boolean
default: true

Number of iterations for the leiden algorithm.

type: number
default: 1

The resolution parameter for the leiden algorithm at the initial stage.

type: number
default: 1

The resolution parameter for the leiden algorithm at the refinement stage.

type: number
default: 0.01

Discard edges with a read count below given value. Set to 1 to disable filtering.

type: number
default: 1

The minimum component size to consider for refinement

type: number
default: 1000

The maximum recursion depth for the refinement algorithm. Set to 1 to disable refinement.

type: number
default: 5

The maximum number of edges to remove between components during the initial stage (iteration == 0) of multiplet recovery.

type: number

The maximum number of edges to remove between components during the refinement stage (iteration > 0) of multiplet recovery.

type: number
default: 4

The maximum number of edges to remove between two components relative to the number of nodes in the smaller of the two when during the initial stage (iteration == 0) of multiplet recovery.

type: number

The maximum number of edges to remove between two components relative to the number of nodes in the smaller of the two when during the refinement stage (iteration > 0) of multiplet recovery.

type: number

The minimum number of nodes in an potential new components in order for it to be pruned.

type: number
default: 100

Components with fewer nodes than this will be filtered from the output data. This is typically not needed. Setting this will disable the automatic size filtering.

type: number

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
  • raw: use the raw counts.
  • log1p: use the log1p-transformed counts.

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

Save the PXL dataset after the analysis stage.

type: boolean

Compute proximity scores

type: boolean
default: true

Compute k-core summary tables for each component

type: boolean

Number of permutations to use when computing the expected proximity scores

type: integer
default: 100

Compute the variance explained by the SVD components

type: boolean
default: true

Number of pivots to use for the SVD decomposition

type: integer
default: 50

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 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+)*

Number of pivots to use for the PMDS layout algorithm. Default: 50. More gives better results, but increases computation time.

type: integer
default: 50

The window size used when computing probability weights for the wpmds layout method. Only used when layout algorithm is set to wpmds.

type: integer
default: 5

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

Use this to force the pipeline to use a different image version in all steps that use the pixelator command. The pipeline is not guaranteed to work when using different pixelator versions.

Save all intermediate results.

type: boolean

Save all intermediate results for the PNA workflow.

type: boolean
default: true

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/pixelator/

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