Nextflow Registry | nf-core/celesta@0.0.0-0c7146d

nf-core/celesta @ 0.0.0-0c7146d

Unsupervised machine learning for cell type identification in multiplexed imaging using protein expression and cell neighborhood information without ground truth

highly_multiplexed_imaging cell_type_identification cell_phenotyping image_analysis mcmicro machine_learning

Latest version: 0.0.0-0c7146d

Total downloads: 4

Source: nf-core/modules

Authors: @LukasHats @ArozHada

Maintainers: @LukasHats @ArozHada

Summary

Unsupervised machine learning for cell type identification in multiplexed imaging using protein expression and cell neighborhood information without ground truth

Get started

Add the following snippet to your workflow script to include this module.

include { CELESTA } from 'nf-core/celesta'

License

MIT License

Process

`Name`	`CELESTA`

Input 4 channels

#1 tuple

`meta` map	Groovy Map containing sample information e.g. `[ id:'test']`
`img_data` file	Quantification table with single cells as rows, markers (e.g. CD3 or CD8 but names do not have to match exactly) and X/Y coordinates as columns `*.csv`

`signature` file	Signature Matrix containing the definition of cell types according to markers `*.csv`

`high_thresholds` file	csv file with user-defined probability high thresholds for anchor cell (row 1) and index cell (row 2) definition `*.csv`

`low_thresholds` file	optional csv file with user-defined probability low thresholds for anchor cell (row 1) and index cell (row 2) definition `*.csv`

Output 3 channels

#1 quality tuple

`meta` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`*quality.csv` file	File with final calculated marker probabilities for inspection, non-deterministic `*.csv`

#2 celltypes tuple

`meta` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`*results.csv` file	File with final celltype annotations concatenated to the original input quantification, due to the mechanism its non-deterministic `*.csv`

#3 versions_celesta tuple

`${task.process}` string	The name of the process
`celesta` string	The name of the tool
`1.0.0` string	The expression to obtain the version of the tool

Tool	Description	Homepage
celesta	Automate unsupervised machine learning cell type identification using both protein expressions and cell spatial neighborhood information	https://github.com/SchapiroLabor/mcmicro-celesta

Version	0.0.0-0c7146d
Commit ID	0c7146d85582628b5d1034504702fa808632b1af
Release Date	08 Apr 2026 18:50:39 (UTC)
Download URL	https://registry.nextflow.io/api/v1/modules/nf-core%2Fcelesta/0.0.0-0c7146d/download
OCI Store URL	https://public.cr.seqera.io/v2/nextflow/plugin/modules/nf-core/celesta/blobs/sha256:97e6060cdae464de1b633e78c01b20da657cd32b8561d679a3baae56786d9718
Size	2.7 KB
Checksum	sha256:97e6060cdae464de1b633e78c01b20da657cd32b8561d679a3baae56786d9718
Downloads	4

Version	Date	Status	Downloads	Size
0.0.0-0c7146d	08 Apr 2026 18:50:39 (UTC)		4	2.7 KB