recipe bioconductor-midashla

R package for immunogenomics data handling and association analysis






MiDAS is a R package for immunogenetics data transformation and statistical analysis. MiDAS accepts input data in the form of HLA alleles and KIR types, and can transform it into biologically meaningful variables, enabling HLA amino acid fine mapping, analyses of HLA evolutionary divergence, KIR gene presence, as well as validated HLA-KIR interactions. Further, it allows comprehensive statistical association analysis workflows with phenotypes of diverse measurement scales. MiDAS closes a gap between the inference of immunogenetic variation and its efficient utilization to make relevant discoveries related to T cell, Natural Killer cell, and disease biology.

package bioconductor-midashla

(downloads) docker_bioconductor-midashla



depends bioconductor-multiassayexperiment:


depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends r-assertthat:


depends r-base:


depends r-broom:


depends r-dplyr:


depends r-formattable:


depends r-hardyweinberg:


depends r-kableextra:


depends r-knitr:


depends r-magrittr:


depends r-qdaptools:


depends r-rlang:


depends r-stringi:


depends r-tibble:




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-midashla

and update with::

   mamba update bioconductor-midashla

To create a new environment, run:

mamba create --name myenvname bioconductor-midashla

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

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