recipe bioconductor-ttgsea

Tokenizing Text of Gene Set Enrichment Analysis

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/ttgsea.html

License:

Artistic-2.0

Recipe:

/bioconductor-ttgsea/meta.yaml

Functional enrichment analysis methods such as gene set enrichment analysis (GSEA) have been widely used for analyzing gene expression data. GSEA is a powerful method to infer results of gene expression data at a level of gene sets by calculating enrichment scores for predefined sets of genes. GSEA depends on the availability and accuracy of gene sets. There are overlaps between terms of gene sets or categories because multiple terms may exist for a single biological process, and it can thus lead to redundancy within enriched terms. In other words, the sets of related terms are overlapping. Using deep learning, this pakage is aimed to predict enrichment scores for unique tokens or words from text in names of gene sets to resolve this overlapping set issue. Furthermore, we can coin a new term by combining tokens and find its enrichment score by predicting such a combined tokens.

package bioconductor-ttgsea

(downloads) docker_bioconductor-ttgsea

versions:

1.10.0-1,  1.10.0-0,  1.8.0-0,  1.6.0-0,  1.2.0-0,  1.0.0-0

depends r-base:

>=4.3,<4.4.0a0

depends r-data.table:

depends r-diagrammer:

depends r-keras:

depends r-purrr:

depends r-stopwords:

depends r-text2vec:

depends r-textstem:

depends r-tm:

depends r-tokenizers:

requirements:

Installation

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-ttgsea

and update with::

   mamba update bioconductor-ttgsea

To create a new environment, run:

mamba create --name myenvname bioconductor-ttgsea

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 quay.io/biocontainers/bioconductor-ttgsea:<tag>

(see `bioconductor-ttgsea/tags`_ for valid values for ``<tag>``)

Download stats

Link to this page

Render an install-with-bioconda badge with the following MarkDown:

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