recipe bioconductor-tuberculosis

Tuberculosis Gene Expression Data for Machine Learning






The tuberculosis R/Bioconductor package features tuberculosis gene expression data for machine learning. All human samples from GEO that did not come from cell lines, were not taken postmortem, and did not feature recombination have been included. The package has more than 10,000 samples from both microarray and sequencing studies that have been processed from raw data through a hyper-standardized, reproducible pipeline.

package bioconductor-tuberculosis

(downloads) docker_bioconductor-tuberculosis



depends bioconductor-annotationhub:


depends bioconductor-data-packages:


depends bioconductor-experimenthub:


depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends curl:

depends r-base:


depends r-dplyr:

depends r-magrittr:

depends r-purrr:

depends r-rlang:

depends r-stringr:

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-tuberculosis

and update with::

   mamba update bioconductor-tuberculosis

To create a new environment, run:

mamba create --name myenvname bioconductor-tuberculosis

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

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