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## Introduction
**nf-core/pixelator** is a bioinformatics best-practice analysis pipeline for analysis of Molecular Pixelation assays.
It takes a samplesheet as input and will process your data using `pixelator` to produce final antibody counts.
1. Build amplicon from input reads ([`pixelator amplicon`](https://github.com/PixelgenTechnologies/pixelator))
2. Read QC and filtering, correctness of the pixel binding sequence sequences ([`pixelator preqc | pixelator adapterqc`](https://github.com/PixelgenTechnologies/pixelator))
3. Assign a marker (barcode) to each read ([`pixelator demux`](https://github.com/PixelgenTechnologies/pixelator))
4. Error correction, duplicate removal, compute read counts ([`pixelator collapse`](https://github.com/PixelgenTechnologies/pixelator))
5. Compute the components of the graph from the edge list in order to create putative cells ([`pixelator graph`](https://github.com/PixelgenTechnologies/pixelator))
6. Call and annotate cells ([`pixelator annotate`](https://github.com/PixelgenTechnologies/pixelator))
7. Analyze the cells for polarization and colocalization ([`pixelator analysis`](https://github.com/PixelgenTechnologies/pixelator))
8. Generate 3D graph layouts for visualization of cells ([`pixelator layout`](https://github.com/PixelgenTechnologies/pixelator))
9. Report generation ([`pixelator report`](https://github.com/PixelgenTechnologies/pixelator))
> [!WARNING]
> Since Nextflow 23.07.0-edge, Nextflow no longer mounts the host's home directory when using Apptainer or Singularity.
> This causes issues in some dependencies. As a workaround, you can revert to the old behavior by setting the environment variable
> `NXF_APPTAINER_HOME_MOUNT` or `NXF_SINGULARITY_HOME_MOUNT` to `true` in the machine from which you launch the pipeline.
## Usage
> [!NOTE]
> If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/usage/installation) on how to set-up Nextflow.Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline) with `-profile test` before running the workflow on actual data.
First, prepare a samplesheet with your input data that looks as follows:
`samplesheet.csv`:
```csv
sample,design,panel,fastq_1,fastq_2
uropod_control,D21,human-sc-immunology-spatial-proteomics,uropod_control_300k_S1_R1_001.fastq.gz,uropod_control_300k_S1_R2_001.fastq.gz
```
Each row represents a sample and gives the design, a panel file and the input fastq files.
Now, you can run the pipeline using:
```bash
nextflow run nf-core/pixelator \
-profile \
--input samplesheet.csv \
--outdir
```
> [!WARNING]
> Please provide pipeline parameters via the CLI or Nextflow `-params-file` option. Custom config files including those provided by the `-c` Nextflow option can be used to provide any configuration _**except for parameters**_; see [docs](https://nf-co.re/docs/usage/getting_started/configuration#custom-configuration-files).
For more details and further functionality, please refer to the [usage documentation](https://nf-co.re/pixelator/usage) and the [parameter documentation](https://nf-co.re/pixelator/parameters).
## Pipeline output
To see the results of an example test run with a full size dataset refer to the [results](https://nf-co.re/pixelator/results) tab on the nf-core website pipeline page.
For more details about the output files and reports, please refer to the
[output documentation](https://nf-co.re/pixelator/output).
## Credits
nf-core/pixelator was originally written for [Pixelgen Technologies AB](https://www.pixelgen.com/) by:
- Florian De Temmerman
- Johan Dahlberg
- Alvaro Martinez Barrio
## Contributions and Support
If you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).
For further information or help, don't hesitate to get in touch on the [Slack `#pixelator` channel](https://nfcore.slack.com/channels/pixelator) (you can join with [this invite](https://nf-co.re/join/slack)).
## Citations
If you use nf-core/pixelator for your analysis, please cite it using the following doi: [10.5281/zenodo.10015112](https://doi.org/10.5281/zenodo.10015112)
An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.
You can cite the `nf-core` publication as follows:
> **The nf-core framework for community-curated bioinformatics pipelines.**
>
> Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.
>
> _Nat Biotechnol._ 2020 Feb 13. doi: [10.1038/s41587-020-0439-x](https://dx.doi.org/10.1038/s41587-020-0439-x).
You can cite the molecular pixelation technology as follows:
> **Molecular pixelation: spatial proteomics of single cells by sequencing.**
>
> Filip Karlsson, Tomasz Kallas, Divya Thiagarajan, Max Karlsson, Maud Schweitzer, Jose Fernandez Navarro, Louise Leijonancker, Sylvain Geny, Erik Pettersson, Jan Rhomberg-Kauert, Ludvig Larsson, Hanna van Ooijen, Stefan Petkov, Marcela González-Granillo, Jessica Bunz, Johan Dahlberg, Michele Simonetti, Prajakta Sathe, Petter Brodin, Alvaro Martinez Barrio & Simon Fredriksson
>
> _Nat Methods._ 2024 May 08. doi: [10.1038/s41592-024-02268-9](https://doi.org/10.1038/s41592-024-02268-9)
