recipe bioconductor-enrichtf

Transcription Factors Enrichment Analysis

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-enrichtf/meta.yaml

As transcription factors (TFs) play a crucial role in regulating the transcription process through binding on the genome alone or in a combinatorial manner, TF enrichment analysis is an efficient and important procedure to locate the candidate functional TFs from a set of experimentally defined regulatory regions. While it is commonly accepted that structurally related TFs may have similar binding preference to sequences (i.e. motifs) and one TF may have multiple motifs, TF enrichment analysis is much more challenging than motif enrichment analysis. Here we present a R package for TF enrichment analysis which combine motif enrichment with the PECA model.

package bioconductor-enrichtf

versions:

1.18.0-0,  1.16.0-0,  1.14.0-0,  1.10.0-0,  1.8.0-0,  1.6.0-1,  1.6.0-0,  1.4.0-0,  1.2.0-0, 

1.18.0-0,  1.16.0-0,  1.14.0-0,  1.10.0-0,  1.8.0-0,  1.6.0-1,  1.6.0-0,  1.4.0-0,  1.2.0-0,  1.0.0-1

depends bioconductor-biocgenerics:

>=0.48.0,<0.49.0

depends bioconductor-bsgenome:

>=1.70.0,<1.71.0

depends bioconductor-clusterprofiler:

>=4.10.0,<4.11.0

depends bioconductor-genomeinfodb:

>=1.38.0,<1.39.0

depends bioconductor-genomicranges:

>=1.54.0,<1.55.0

depends bioconductor-iranges:

>=2.36.0,<2.37.0

depends bioconductor-jaspar2018:

>=1.1.0,<1.2.0

depends bioconductor-motifmatchr:

>=1.24.0,<1.25.0

depends bioconductor-pipeframe:

>=1.18.0,<1.19.0

depends bioconductor-rtracklayer:

>=1.62.0,<1.63.0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends bioconductor-tfbstools:

>=1.40.0,<1.41.0

depends r-base:

>=4.3,<4.4.0a0

depends r-ggplot2:

depends r-ggpubr:

depends r-heatmap3:

depends r-magrittr:

depends r-r.utils:

depends r-rmarkdown:

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-enrichtf

and update with::

   mamba update bioconductor-enrichtf

To create a new environment, run:

mamba create --name myenvname bioconductor-enrichtf

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-enrichtf:<tag>

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

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