recipe r-alakazam

Provides methods for high-throughput adaptive immune receptor repertoire sequencing (AIRR-Seq; Rep-Seq) analysis. In particular, immunoglobulin (Ig) sequence lineage reconstruction, lineage topology analysis, diversity profiling, amino acid property analysis and gene usage. Citations: Gupta and Vander Heiden, et al (2017) <doi:10.1093/bioinformatics/btv359>, Stern, Yaari and Vander Heiden, et al (2014) <doi:10.1126/scitranslmed.3008879>.






package r-alakazam

(downloads) docker_r-alakazam



depends bioconductor-biostrings:


depends bioconductor-genomicalignments:


depends bioconductor-iranges:


depends libgcc-ng:


depends libstdcxx-ng:


depends r-airr:


depends r-ape:

depends r-base:


depends r-dplyr:


depends r-ggplot2:


depends r-igraph:


depends r-matrix:

depends r-progress:

depends r-rcpp:


depends r-readr:

depends r-rlang:

depends r-scales:

depends r-seqinr:

depends r-stringi:

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 r-alakazam

and update with::

   mamba update r-alakazam

To create a new environment, run:

mamba create --name myenvname r-alakazam

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

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