Nextflow Registry | nf-core/mobster@0.0.0-6c4ed3a

nf-core/mobster @ 0.0.0-6c4ed3a

Subclonal deconvolution of cancer genome sequencing data.

subclonal deconvolution genomics cancer evolution

Latest version: 0.0.0-6c4ed3a

Total downloads: 2

Source: nf-core/modules

Authors: @elena-buscaroli

Maintainers: @elena-buscaroli

Subclonal deconvolution of cancer genome sequencing data.

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

include { MOBSTER } from 'nf-core/mobster'

MIT License

Process

`Name`	`MOBSTER`

Input 1 channel

#1 tuple

`meta` map	Groovy Map containing sample information e.g. `[ id:'sample1' ]`
`rds_join` file	Either a .rds object of class mCNAqc or a .csv mutations table `*.{rds,csv}`

Output 7 channels

#1 mobster_rds tuple

`meta` map	Groovy Map containing sample information e.g. `[ id:'sample1' ]`
`*_mobster_fit.rds` file	Full mobster fit as an .rds object `*_mobster_fit.rds`

#2 mobster_best_rds tuple

`meta` map	Groovy Map containing sample information e.g. `[ id:'sample1' ]`
`*_mobster_best_fit.rds` file	Best mobster fit as an .rds object `*_mobster_best_fit.rds`

#3 versions_mobster

`versions.yml` file	File containing software versions `versions.yml`

#4 mobster_report_pdf tuple

`meta` map	Groovy Map containing sample information e.g. `[ id:'sample1' ]`
`*_mobster_report.pdf` file	Final report plots as a .pdf file `*_mobster_report.pdf`

#5 mobster_report_png tuple

`meta` map	Groovy Map containing sample information e.g. `[ id:'sample1' ]`
`*_mobster_report.png` file	Final report plots as a .png file `*_mobster_report.png`

#6 mobster_report_rds tuple

`meta` map	Groovy Map containing sample information e.g. `[ id:'sample1' ]`
`*_mobster_report.rds` file	Final report plots as an .rds object `*_mobster_report.rds`

#7 mobster_best_plots_rds tuple

`meta` map	Groovy Map containing sample information e.g. `[ id:'sample1' ]`
`*_mobster_best_plots.rds` file	Final plots as an .rds object `*_mobster_best_plots.rds`

Tool	Description	Homepage
mobster	mobster is a package that implements a model-based approach for subclonal deconvolution of cancer genome sequencing data. The package integrates evolutionary theory (i.e., population) and Machine-Learning to analyze (e.g., whole-genome) bulk data from cancer samples. This analysis relates to clustering; we approach it via a maximum-likelihood formulation of Dirichlet mixture models, and use bootstrap routines to assess the confidence of the parameters.	https://caravagnalab.github.io/mobster/

Version	0.0.0-6c4ed3a
Commit ID	6c4ed3a220310b905a1fc9d04f05be2e0837142b
Release Date	23 Apr 2026 15:32:03 (UTC)
Download URL	https://registry.nextflow.io/api/v1/modules/nf-core%2Fmobster/0.0.0-6c4ed3a/download
OCI Store URL	https://public.cr.seqera.io/v2/nextflow/plugin/modules/nf-core/mobster/blobs/sha256:6b6de93b82cca74275fbb4a8879052a9a3002b72893450585fe061d849bf5a8a
Size	5.0 KB
Checksum	sha256:6b6de93b82cca74275fbb4a8879052a9a3002b72893450585fe061d849bf5a8a
Downloads	1

Version	Date	Status	Downloads	Size
0.0.0-6c4ed3a	23 Apr 2026 15:32:03 (UTC)		1	5.0 KB
0.0.0-0c7146d	08 Apr 2026 19:18:56 (UTC)