recipe r-scoper

Provides a computational framework for identification of B cell clones from Adaptive Immune Receptor Repertoire sequencing (AIRR-Seq) data. Three main functions are included (identicalClones, hierarchicalClones, and spectralClones) that perform clustering among sequences of BCRs/IGs (B cell receptors/immunoglobulins) which share the same V gene, J gene and junction length. Nouri N and Kleinstein SH (2018) <doi: 10.1093/bioinformatics/bty235>. Nouri N and Kleinstein SH (2019) <doi: 10.1101/788620>. Gupta NT, et al. (2017) <doi: 10.4049/jimmunol.1601850>.



AGPL / AGPL-3.0-only



package r-scoper

(downloads) docker_r-scoper



depends libgcc-ng:


depends libstdcxx-ng:


depends r-alakazam:


depends r-base:


depends r-data.table:

depends r-doparallel:

depends r-dplyr:


depends r-foreach:

depends r-ggplot2:


depends r-rcpp:


depends r-rlang:

depends r-scales:

depends r-shazam:


depends r-stringi:

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 r-scoper

and update with::

   mamba update r-scoper

To create a new environment, run:

mamba create --name myenvname r-scoper

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 `r-scoper/tags`_ for valid values for ``<tag>``)

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