recipe bioconductor-scpipe

Pipeline for single cell multi-omic data pre-processing



GPL (>= 2)



A preprocessing pipeline for single cell RNA-seq/ATAC-seq data that starts from the fastq files and produces a feature count matrix with associated quality control information. It can process fastq data generated by CEL-seq, MARS-seq, Drop-seq, Chromium 10x and SMART-seq protocols.

package bioconductor-scpipe

(downloads) docker_bioconductor-scpipe



depends bioconductor-annotationdbi:


depends bioconductor-basilisk:


depends bioconductor-biocgenerics:


depends bioconductor-biomart:


depends bioconductor-biostrings:


depends bioconductor-dropletutils:


depends bioconductor-genomicalignments:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-multiassayexperiment:






depends bioconductor-rhtslib:


depends bioconductor-rsamtools:


depends bioconductor-rsubread:


depends bioconductor-rtracklayer:


depends bioconductor-s4vectors:


depends bioconductor-singlecellexperiment:


depends bioconductor-summarizedexperiment:


depends bioconductor-zlibbioc:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-data.table:

depends r-dplyr:

depends r-flexmix:

depends r-ggally:

depends r-ggplot2:

depends r-glue:


depends r-hash:

depends r-magrittr:

depends r-mass:

depends r-matrix:


depends r-mclust:

depends r-purrr:

depends r-rcpp:


depends r-reshape:

depends r-reticulate:

depends r-rlang:

depends r-robustbase:

depends r-scales:

depends r-stringr:

depends r-testthat:

depends r-tibble:

depends r-tidyr:



You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-scpipe

and update with::

   mamba update bioconductor-scpipe

To create a new environment, run:

mamba create --name myenvname bioconductor-scpipe

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-scpipe/tags`_ for valid values for ``<tag>``)

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