recipe bioconductor-tin

Transcriptome instability analysis







biotools: tin, doi: 10.4137/CIN.S31363

The TIN package implements a set of tools for transcriptome instability analysis based on exon expression profiles. Deviating exon usage is studied in the context of splicing factors to analyse to what degree transcriptome instability is correlated to splicing factor expression. In the transcriptome instability correlation analysis, the data is compared to both random permutations of alternative splicing scores and expression of random gene sets.

package bioconductor-tin

(downloads) docker_bioconductor-tin



depends bioconductor-impute:


depends r-aroma.affymetrix:

depends r-base:


depends r-data.table:

depends r-squash:

depends r-stringr:

depends r-wgcna:



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-tin

and update with::

   mamba update bioconductor-tin

To create a new environment, run:

mamba create --name myenvname bioconductor-tin

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

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