pixelator
nf-core/pixelator
Pipeline for analysis of Proximity Network Assay data
Key tools
Run it
nfclaw run pixelator --input samplesheet.csv --outdir results --technology <technology> -profile dockernextflow run pipelines/pixelator/upstream -profile docker --input samplesheet.csv --outdir results --technology <technology>nfclaw run pixelator --demo --outdir results # adds the upstream test profile (-profile test,docker)Inputs
| column | type | required | allowed values | constraints |
|---|---|---|---|---|
pool | string | no | matches ^\S+$ | |
hash_index | integer | no | ||
sample | string | yes | matches ^\S+$ | |
sample_alias | string | yes | ||
condition | string | yes | ||
design | string | yes | matches ^\S+$ | |
panel | string | no | matches ^\S+$ | |
panel_file | string | no | matches ^$|^\S+\.(csv|tsv|ya?ml)$ | |
fastq_1 | string | yes | matches ^\S+\.f(ast)?q\.gz$ | |
fastq_2 | string | no | matches ^\S+\.f(ast)?q\.gz$ |
--input must match ^\S+\.(csv|tsv|yml|yaml)$.
For tabular CSV/TSV input, use this header (the columns the schema requires); fill each value per the table above and reference.md (no example value is invented here):
sample,sample_alias,condition,design,fastq_1Any of the optional columns above may be appended to the header when your data needs them: pool, hash_index, panel, panel_file, fastq_2.
From data files. --input may also be the data files — a directory (searched recursively), a quoted glob, or files (--input once per file) — from which nfclaw writes this samplesheet: sample from file names; fastq_1/fastq_2 from FastQ files (mates paired by _R1/_R2, or by _1/_2 when their read names show they are mates); panel_file from files matching their patterns, by sample name. Set the required columns no file determines with --sheet-set COLUMN=VALUE (a constant or a {sample}/{lane} template): sample_alias (string); condition (string); design (matching ^\S+$). Preview it with --check; a run records it in <outdir>/provenance/ for replay.
Resources
Resource requests follow the pipeline's configs and selected profiles. nf-core's resource labels often assume a server — a single step can request far more memory than a workstation has, and retry rules can increase requests. If a run fails with Process requirement exceeds available memory (or CPUs), cap every request, and every retry, at what this machine actually has:
nfclaw run pixelator --input samplesheet.csv --outdir results --technology <technology> -profile docker \ --limit-cpus 4 --limit-memory 15.GBnfclaw turns those into Nextflow's process.resourceLimits and passes them as a -c config — the mechanism nf-core prescribes for exactly this (docs). Set them to the machine's real capacity. --limit-time DURATION also caps how long any one task may run: a task that needs longer is stopped, and so is every retry, so set it only as a deliberate ceiling, never as a guess at how long the analysis takes. The generated config is kept in <outdir>/provenance/, so commands.sh replays the run under the same ceiling.
Nextflow engine
This release declares nextflowVersion = '!>=25.10.4'.
To pin this release's declared minimum engine — useful when a newer Nextflow has incompatible config parsing:
nfclaw run pixelator ... --nxf-ver 25.10.4--nxf-ver is recorded in <outdir>/provenance/, so the replay uses the same engine. See known-issues.
Demo
nfclaw run pixelator --demo --outdir results # adds the upstream test profile (-profile test,docker)Samplesheet
A CSV with this header (the columns the schema requires). Fill each value per the constraints below; optional columns from the table may be appended.
sample,sample_alias,condition,design,fastq_1| Column | Type | Required | Allowed / constraints |
|---|---|---|---|
pool | string | optional | matches ^\S+$ |
hash_index | integer | optional | — |
sample | string | required | matches ^\S+$ |
sample_alias | string | required | — |
condition | string | required | — |
design | string | required | matches ^\S+$ |
panel | string | optional | matches ^\S+$ |
panel_file | string | optional | matches ^$|^\S+\.(csv|tsv|ya?ml)$ |
fastq_1 | string | required | matches ^\S+\.f(ast)?q\.gz$ |
fastq_2 | string | optional | matches ^\S+\.f(ast)?q\.gz$ |
Required parameters
--inputstring (file path)Path to comma-separated file containing information about the samples in the experiment.
Constraint · matches ^\S+\.(csv|tsv|yml|yaml)$
--outdirstring (directory path)The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.
--technologystringThe technology used to process the samples
proxiome-v1proxiome-v2hashed_samplesnonhashed_samplesParameter explorer
84 parameters · 13 groupsEvery parameter from the pinned nextflow_schema.json. nfclaw checks explicit values before launch; complex rules use the pinned pipeline's runtime validation. Search, filter by group, and expand any parameter for its default, allowed values and constraints.
69 parameters · 15 hidden
Experiment Summary options1
Skip experiment summary generation
Generic options3
Display the help message.
Display the full detailed help message.
Display hidden parameters in the help message (only works when --help or --help_full are provided).
Global Config options5
Override the container image to use for the experiment summary step.
Override the container image reference to use for all steps using the pixelator command.
Save all intermediate results.
Save all JSON report and metadata files generated by pixelator.
The technology used to process the samples
Input Output options4
Email address for completion summary.
Path to comma-separated file containing information about the samples in the experiment.
Path to a local or remote directory that is the "current working directory" for relative paths defined in the input samplesheet
The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.
Pna Amplicon options9
Enable filtering of amplicons with UMI sequences that show similarity to the LBS sequence.
The allowed error-rate in a semi-global alignment of a UMI sequence with the LBS regions. The error rate is defined as a percentage of UMI length. [0.0<=x<=1.0]
The minimum overlap required in a semi-global alignment of a UMI sequence with the LBS regions. Reads with less overlap will not be removed by the LBS filter. [4<=x<=28]
Enable filtering of amplicons with low complexity UMI sequences.
The threshold for determining if a UMI sequence is of low complexity and will be removed. [0.5<=x<=1.0]
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]
Minimum average quality a read must have. Pass 0 to disable quality filtering.
Remove PolyG sequences (length of 10 or more)
Save intermediate amplicon reads generated from the raw input reads.
Pna Analysis options6
Compute k-core summary tables for each component
Compute proximity scores
Compute the variance explained by the SVD components
Number of pivots to use for the SVD decomposition
Save the PXL dataset after the analysis stage.
Skip analysis step
Pna Collapse options3
The algorithm to use for collapsing.
The number of mismatches allowed when collapsing (adjacency)
Save an intermediate parquet file containing collapsed read information.
Pna Demux options7
The number of mismatches allowed in marker barcodes.
The target number of reads in a single file of the partitioned demux output.
The maximum number of chunks that the demuxed ouput for each umi region will be split into
The demux and collapsing strategy to use
Save intermediate FASTQC read files containing all reads that do not contain valid antibody barcodes.
Save intermediate parquet files containing embeddings of all reads that contain valid antibody barcodes.
Save intermediate FASTQC read files containing all reads that contain valid antibody barcodes.
Pna Denoise options9
Neighborhood radius in graph steps for ACE denoising.
The inflate factor for the number of nodes from over-expressed markers to be removed from the one-core layer of a component
All retained PLS score columns must exceed this value.
The p-value threshold for the a marker to be considered significantly over-expressed in the one-core layer of a component
Remove nodes in the peripheral-like partition using adaptive core expansion (ACE).
Activate the one-core graph denoising algorithm
Run PLS-on-coreness denoising and retain the largest connected component after filtering.
Save the PXL dataset after the denoise stage.
Skip denoise step
Pna Graph options13
Components with more nodes than this will be filtered from the output data. Set to null to enable automatic size filtering based on the data.
Components with fewer nodes than this will be filtered from the output data. Set to null to enable automatic size filtering based on the data.
Activate edge cycle verification to remove edges from well connected regions that are not part of cycles in the graph.
The resolution parameter for the leiden algorithm at the initial stage.
The maximum number of edges to remove between components during the initial stage (iteration == 0) of multiplet recovery.
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.
The maximum recursion depth for the refinement algorithm. Set to 1 to disable refinement.
Discard edges with a read count below given value. Set to 1 to disable filtering.
Activate the multiplet recovery using leiden community detection
The resolution parameter for the leiden algorithm at the refinement stage.
The maximum number of edges to remove between components during the refinement stage (iteration > 0) of multiplet recovery.
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.
Save the PXL dataset after the graph stage.
Pna Layout options5
Select a layout algorithm to use. This can be specified as a comma separated list to compute multiple layouts. Possible values are: pmds, pmds_3d, wpmds, wpmds_3d, coarsened_pmds_3d.
Skip adding marker counts to the layout.
Number of pivots to use for the PMDS layout algorithm. Default: 50. More gives better results, but increases computation time.
The window size used when computing probability weights for the wpmds layout method. Only used when layout algorithm is set to wpmds.
Skip layout step
Pna Sample Calling options4
Enrichment threshold for sample calling.
Remove antibodies that are incompatible with their component's called sample.
Save components that could not be confidently assigned to any sample to a separate pxl file.
Save the PXL dataset after the sample calling stage.
Outputs
Results land in --outdir; the files and directory layout depend on the selected workflow, parameters and publication settings. Run metadata is normally placed in <outdir>/pipeline_info/ (execution report, software versions), when those outputs are enabled. nfclaw run also writes <outdir>/provenance/ with the exact params file and the run log, <outdir>/provenance/logs/run.log — the whole launch, whose last line states the outcome (Nextflow's own log is <outdir>/.nextflow.log); unless --no-provenance it adds a run manifest (pinned version, commit and exact command), input/output SHA-256 checksums, and a replayable commands.sh.
The exact output files and directory layout for this release are documented upstream: github.com/nf-core/pixelator/blob/6.0.0/docs/output.md
Check a run — in the foreground or the background — with nfclaw status <outdir>: success, still running, how it ended (with the error), or stopped without an outcome; exit 0 success, 3 running, 1 otherwise.