Nextflow Registry | nf-core/cellbender/removebackground@0.0.0-6c4ed3a

nf-core/cellbender/removebackground @ 0.0.0-6c4ed3a

Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data

single-cell scRNA-seq ambient RNA removal

Latest version: 0.0.0-6c4ed3a

Total downloads: 8

Source: nf-core/modules

Authors: @nictru

Maintainers: @nictru

Module to use CellBender to estimate ambient RNA from single-cell RNA-seq data

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

include { CELLBENDER_REMOVEBACKGROUND } from 'nf-core/cellbender/removebackground'

MIT License

Process

`Name`	`CELLBENDER_REMOVEBACKGROUND`

Input 1 channel

#1 tuple

`meta` map	Groovy Map containing sample information e.g. [ id:'test' ]
`h5ad` file	AnnData file containing unfiltered data (with empty droplets) `*.h5ad`

Output 10 channels

#1 h5 tuple

`meta` map	Groovy Map containing sample information
`${prefix}.h5` file	Full count matrix as an h5 file, with background RNA removed. This file contains all the original droplet barcodes. `*.h5`

#2 log tuple

`meta` map	Groovy Map containing sample information
`${prefix}.log` file	Log file produced by the cellbender remove-background run. `*.log`

#3 pdf tuple

`meta` map	Groovy Map containing sample information
`${prefix}.pdf` file	PDF file that provides a standard graphical summary of the inference procedure. `*.pdf`

#4 report tuple

`meta` map	Groovy Map containing sample information
`${prefix}_report.html` file	HTML report including plots and commentary, along with any warnings or suggestions for improved parameter settings. `*.html`

#5 metrics tuple

`meta` map	Groovy Map containing sample information
`${prefix}_metrics.csv` file	Metrics describing the run, potentially to be used to flag problematic runs \| when using CellBender as part of a large-scale automated pipeline. `*.csv`

#6 barcodes tuple

`meta` map	Groovy Map containing sample information
`${prefix}_cell_barcodes.csv` file	CSV file containing all the droplet barcodes which were determined to have a > 50% posterior probability of containing cells. \| Barcodes are written in plain text. This information is also contained in each of the above outputs, \| but is included as a separate output for convenient use in certain downstream applications. `*.csv`

#7 checkpoint tuple

`meta` map	Groovy Map containing sample information
`ckpt.tar.gz` file	Checkpoint file which contains the trained model and the full posterior. `*.ckpt`

#8 filtered_h5 tuple

`meta` map	Groovy Map containing sample information
`${prefix}_filtered.h5` file	Full count matrix as an h5 file, with background RNA removed. This file contains only the droplet barcodes which were determined to have a > 50% posterior probability of containing cells. `*.h5`

#9 posterior_h5 tuple

`meta` map	Groovy Map containing sample information
`${prefix}_posterior.h5` file	The full posterior probability of noise counts. This is not normally used downstream. `*.h5`

#10 versions_cellbender tuple

`${task.process}` string	The name of the process
`cellbender` string	The name of the tool
`cellbender --version` eval	The expression to obtain the version of the tool

Tool	Description	Homepage
cellbender	CellBender is a software package for eliminating technical artifacts from high-throughput single-cell RNA sequencing (scRNA-seq) data.	n/a

Version	0.0.0-6c4ed3a